Abstract

The field of soft robotics has been significantly advanced with the recent developments of pneumatic techniques, soft materials, and high-precision motion control. While comprehensive motions can be achieved by sophisticated soft robots, multiple coordinated pneumatic controls are usually required to achieve even the simplest motions. Furthermore, most soft robotics are lacking the ability to sense the environment and provide feedback to the pneumatic control system. In this work, we design a twining plant inspired soft-robotic spiral gripper that requires only one single pneumatic control to perform the twining motion and to firmly hold onto a target object. The soft-robotic spiral gripper has an embedded high-birefringence fiber optic twisting sensor to provide critical information, including twining angle, presence of external perturbation, and physical parameter of the target object. Furthermore, finite element analyses (FEA) in parametric studies of the spiral gripper are performed for module design optimization. The unique single pneumatic channel design enables easy manipulation of the soft spiral gripper with a maximum of 540° twining angle and allows a firm grip of a target object as small as 1-mm in diameter. The embedded fiber optic sensor provides useful information of the target object as well as the twining angle of the soft robotic spiral gripper with high twining angle sensitivity of 0.03nm. The unique fiber-optic sensor embedded single-channel pneumatic spiral gripper that is made from non-toxic silicone rubber allows parallel and soft gripping of elongated objects located in a confined area, which is an essential building block for twining and twisting motions in soft robot.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Soft pneumatic robots have gained lots of attention as a promising alternative to hard rigid robots due to their deformability, flexibility, low-cost, and great environmental compatibility [1,2]. It is of particular interest in areas where human interactions and fragile objects are involved. The designs of soft robots usually are inspired by living organisms that move around and adapt to their surroundings [37]. For example, locomotion and grasping in soft robots have been inspired by octopus arms [6], where cables and shape memory alloy springs are used to enable elongation, shortening, and bending of the robotic arm. Crawling robots inspired by the squirming and moving motion in inchworm have also been demonstrated [7], which combines pneumatic suction cups and pneumatic body to mimic the worm-like motion. Soft robotic grippers have been extremely useful in healthcare treatment and automated industrial processes such as advanced assembly and food handling. Among existing soft robotic research, there are two major types of pneumatic soft robotic grippers – robotic hands [8] and robotic tentacles [5]. Robotic hands mimic a human’s palm along with fingers for gripping an object with an open and close motion, while robotic tentacles mimic octopus’s arms to wrap around the target object. However, both soft robotic gripper designs require a large operation space to allow the soft robotic gripper to gain access to the target object and the motions involve multiple coordinated pneumatic channels.

Although soft robots with sophisticated movements can be achieved, the development of sensors embedded in soft robots is still lacking behind. Sensors are an essential component to provide accurate pneumatic control, to acquire information on the target object, and to detect unusual external disturbance [9]. Stretchable electronic sensors for soft robotics could be achieved through embedded 3D printing [10], but the embedded 3D printing process is not trivial and still under development. Furthermore, the connections between the soft robot body and the conventional rigid electronics are physically vulnerable and are prone to breakage. Also, power loss and heavy weight of copper wires for transmitting sensor signals to the processor limits the operation distance and mobility of the soft robot [1113]. More importantly, the materials used in stretchable electronics may not be safe for human or for operating in magnetic/electrostatic discharging environments.

Glass fiber optic sensors offer a lightweight, small size, low loss, multiplexing, and fast response solution that has been widely studied and deployed in various fields including biomedical, civil engineering, and aerospace engineering [1417]. The downside of glass fiber optic sensors that hinders its application in soft robotics is the lack of elasticity of glass fiber. While polymer fiber offers a promising solution to stretchability [18,19], it may not inherit all the unique advantages from glass fiber optic sensors. Furthermore, due to the Young’s Modulus difference between polymer fiber and the soft robot’s silicone material, the polymer fiber will still experience delamination when directly embedded in the soft robot without a careful embedding design. Recently, research have shown that it is possible to embed glass fiber optic sensors in soft robots through unique embedding architecture and mechanical design [9].

In this paper, we present the design, simulation, and experimental demonstration of a twining plant inspired soft spiral gripper with an embedded fiber optic sensor. Unlike other grippers, the demonstrated spiral gripper can operate in a confined space and require only one single pneumatic control. The design is inspired by the twining plant, which can securely grip onto a small target in a confined operation space. As the twining plant grows, the tendrils climb and twist along a stem or a trunk, holding the object firmly, which is illustrated in Fig. 1(a). If the growing tendrils are regarded as a fixed-length soft robot, as shown in Fig. 1(b)-(c), the climbing process, therefore, turns into a twining motion through twisting. The embedded fiber optic sensor is a high-birefringence (HiBi) fiber in a Sagnac loop configuration to effectively sense the twisting angle, the diameter of the target object, as well as the presence of external perturbation.

 figure: Fig. 1.

Fig. 1. (a) Illustration of the twining motion in twining plant; (b) Soft spiral gripper before actuation; (c) Actuated soft spiral gripper holding a flower.

Download Full Size | PPT Slide | PDF

2. Model designing via computational analysis

2.1 Initial design

Figure 2 shows the design model of the soft spiral gripper with fiber optic sensor embedded. As shown in Fig. 2(a)-(b), the soft spiral gripper consists of a cylindrical elastic body made of silicone rubber (light gray) to host the helical pneumatic channel (green) for enabling twining motion, and an HiBi fiber optic sensor (yellow) is embedded in an elastic spine (brown) to eliminate delamination of the fiber optic sensor.

 figure: Fig. 2.

Fig. 2. (a) Top view of the soft spiral gripper (b) 3D view of the soft spiral gripper (c) 3D-printed molds for fabricating the soft spiral gripper.

Download Full Size | PPT Slide | PDF

The spiral gripper molds are 3D-printed as illustrated in Fig. 2(c). Two 13.5-mm diameter half cylindrical walls with 85-mm in height are used as the mold for the soft spiral gripper body for easy demolding, as shown in light blue. The base (red) has a circular groove for fixing the two half cylindrical walls in position. The 3D printed molds can be reused for reproducing the spiral gripper.

A helical mold is attached to the base for creating the helical pneumatic channel as shown in red. The helical mold (i.e. for the helical pneumatic channel) is characterized by the azimuthal angle, θ. The azimuthal angle (θ) is defined as the direction change (i.e. angle between two vectors) between the orthogonal projection (point $A^{\prime}$ in Fig. 2(c)) of the top end of the helical pneumatic channel mold (point A) on x-y plane and the vector connecting the origin and the bottom end of the helical pneumatic channel mold (point B). The azimuthal angle is the total direction change of helical pneumatic channel before actuation that can be larger than 360° as indicated as green in Fig. 2(c). A recent study [20] shows that a pneumatic channel with a smaller diameter results in a larger twining angle with the same body length. Therefore, we tested several 3D printers and found the most promising one we have access to - MakerBot Replicator 5, is capable of printing a uniform helical mold with the diameter as small as 2 mm and 80 mm in height without breaking. As our test also shows, a pneumatic channel wall (i.e. the distance between the pneumatic channel and the outside of the gripper body) of 3 mm not only allows a larger twining angle under the same pressure but also prevents the gripper from bursting during actuation. By considering the 3D printer capability, we will start with a spiral gripper model that has a 2-mm pneumatic channel diameter, 85-mm body length, 80-mm pneumatic channel height, and 3-mm pneumatic channel wall thickness in both the simulation and experiment. In the following simulation and experiment, we will focus on the optimization of the design parameter including the azimuthal angle of the pneumatic channel, Young’s modulus of the elastic spine, and the gripper body, as well as pneumatic pressure to achieve a secure grip.

2.2 Model optimization

Finite element analyses (FEA) in parametric studies are performed for model design optimization on Abaqus CAE with the Standard/Explicit model. The spiral gripper body is made from a 1:1 mixture of Ecoflex 00-10 and 00-30 that has Young’s modulus of 0.0262 MPa. The well-established nonlinear hyperelastic model, Mooney-Rivlin, has been demonstrated to be the most precise model for various Ecoflex silicone material we used in the spiral gripper, with incompressibility constraints being considered [21]. The first-order Mooney-Rivlin model has N = 1, C10 = 0.0418 MPa, and C01 = 0.0106 MPa.

First, two preliminary experiments are performed to investigate the maximum actuation pressure the spiral gripper can support without breakage and the optimal number of twining cycles to achieve a secure grip. It is observed that the breakage point of the spiral gripper is around 0.675 MPa. Therefore, we set the actuation pressure in the simulation to be 0.67 MPa (97psi). To study the optimal number of twining cycles, we experimentally test several twining models and found out that 1.5-cycles is the optimized number of cycles for securely gripping onto the target object. This is because spiral gripper with less than 1.5 cycles has a loose grip, while gripper with close to 2 cycles makes it hard to twining around the target object at the gripper tip. Next, we study the relationship between the azimuthal angle of the helical pneumatic channel and the maximum twining angle of the soft spiral gripper when actuated at 0.67MPa (i.e. the maximum pressure before breakage occurs). Where the twining angle is defined as the direction change between the top and bottom of the spiral gripper after actuation. The insets at the bottom of Fig. 3 show the corresponding simulation results of the actuated soft spiral gripper with the azimuthal angle of 180°, 270°, 360°, 450°, and 540°. The twining angle increases linearly with the increase in azimuthal angle of the helical pneumatic channel. It shows that azimuthal angle of 450° provides a twining angle of 540°, corresponding to 1.5 cycles of a full twining around a target object, i.e. the optimal number of cycles for a firm grip of the target object. Therefore, the helical pneumatic channel with 450° azimuthal angle is used to achieve a 540° twining of the soft spiral gripper under 0.67 MPa in the final design.

 figure: Fig. 3.

Fig. 3. Relationship between azimuthal angle of the helical pneumatic channel and maximum twining angle of the soft spiral gripper with Young’s modulus (YM) ratio between the gripper body and the elastic spine of 1:1, 1:2, 1:3, and 1:4.

Download Full Size | PPT Slide | PDF

The effect on the twining angle due to the difference in Young’s modulus ratio between the gripper body and the elastic spine is also studied in Fig. 3 by setting the ratio to be 1:1, 1:2, 1:3, and 1:4. The Mooney-Rivlin model parameter of material hardness used for simulation are matched to Young’s modulus ratio. For the same azimuthal angle, the variation in Young’s modulus ratio between the gripper body and the elastic spine has less than 2.6% or 14° change in the total twining angle of the robot, which is negligible in the twining angle design. Furthermore, as observed in our preliminary experiment, Young’s modulus ratio between the gripper body and the elastic spine has a significant effect on the minimum target object diameter that the spiral gripper can hold. When the soft spiral gripper is actuated, there is a hollow area at the center along the z-axis (twining axis) where the target object is going to be located. In the simulation, all the nodes along the z-axis are projected onto the x-y plane to observe the center hollow area, as shown by the red circles and red arrow markers in Fig. 4. Azimuthal angle of 450° and pneumatic actuation pressure of 0.67MPa are used in the simulation. It is observed that the nodes distributed denser around the hollow region while it is sparer in the peripheral area due to the larger expansion in the outer region during the inflation of the pneumatic channel. The hollow region is measured to be 0.8 mm, 0.9 mm, 1.0 mm, and 1.3 mm in diameter for Young’s modulus ratio of 1:1, 1:2, and 1:3, and 1:4, respectively, as shown in Fig. 4. A harder elastic spine (larger Young’s modulus) results in a larger hollow center region because a harder material makes it more difficult to bend around circle with a smaller diameter. The hollow area determines the smallest object that the soft spiral gripper could securely hold when actuated.

 figure: Fig. 4.

Fig. 4. Hollow area diameter of the actuated soft spiral gripper changes with Young’s modulus ratio between spiral gripper body and the elastic spine. (a) 1:1 ratio result in hollow area with a 0.8-mm diameter; (b) 1:2 ratio result in hollow area with a 0.9-mm diameter; (c) 1:3 ratio result in hollow area with a 1.0-mm diameter hollow area; (d)1:4 ratio result in hollow area with a 1.3-mm diameter hollow area.

Download Full Size | PPT Slide | PDF

Although a softer elastic spine seems to provide the smaller gripping diameter, the elongation of the soft spiral gripper cannot be ignored. For example, Dragon Skin-10 has Young’s modulus of 0.085 MPa [22] is able to be stretched by 663%, while Ecoflex 00-30 with Young’s modulus around 0.027 MPa [23] is able to be stretched by 900%. As the soft spiral gripper is actuated, its spiral motion results in elongation of the elastic spine and a contraction of the overall gripper due to the displacement of the gripper tip. Large elongation of the elastic spine potentially results in delamination of the fiber optic sensor and leads to unreliable sensing performance [9]. To prevent delamination of the fiber optic sensor from the elastic spine, large displacement of the tip (i.e. large contraction of the spiral gripper) is needed to minimize the elongation of the elastic spine. The displacement of the spiral gripper tip is measured and summarized in Table 1. It is observed that a higher Young’s modulus ratio results in a greater tip displacement and a smaller elongation. It is worth mentioning that although Young’s modulus ratio of 1:4 gives the greatest tip displacement, the elastic spine is vulnerable to detach from the spiral gripper body in the actuation process due to the large difference in Young’s modulus. Therefore, taking the above criteria into consideration, Young’s modulus ratio of 1:3 is the optimized Young’s modulus ratio to provide a small hollow area while preventing delamination.

Tables Icon

Table 1. Comparison of different material ratio under the 450° azimuthal angle model.

Finally, we investigate the ability to tune the twining angle through the use of different pneumatic pressure to precisely control the way that the soft spiral gripper can hold onto the target object. With the azimuthal angle of the helical pneumatic channel at 450° and pneumatic pressure varying between 0.1 to 0.675 MPa, which is the safe actuation range of the spiral gripper before breakage occurs (i.e. simulation would automatically stop at the pressure limit), the resultant twining angle and pressure limit are simulated and shown in Fig. 5 and Table 1, respectively. As shown in Fig. 5, the twining angle increases with the rising pneumatic pressure. While the twining angle is similar for soft spiral gripper with Young’s modulus ratio of 1:2, 1:3, and 1:4. The curve for 1:1 Young’s modulus ratio shows a larger twining angle can be obtained at low pressure setting because the material is so soft that twining can easily be achieved even in low pressure. In all cases, the twining angle increases significantly as the pressure approaches 0.55 MPa, and then gradually reaches their maximum allowable pressure before bursting. The insert in Fig. 5 is the enlarged region of the end stage, showing that the maximum allowable pressure is similar for all the cases. The maximum allowable pneumatic pressure and the resultant maximum twining angle are summarized in Table 1.

 figure: Fig. 5.

Fig. 5. Relationship between the applied pneumatic pressure and the resultant twining angle under different Young’s modulus ratio.

Download Full Size | PPT Slide | PDF

3. Experimental design and fabrication

Based on the simulation results above, the design parameters can be determined as shown in Fig. 2. The 3D printed molds (Fig. 2(c)) are used to fabricate the soft spiral gripper (Fig. 2(a)-(b)). The soft spiral gripper body is made of a mix of Ecoflex 00-10 and Ecoflex 00-30 with a 1:1 mass ratio, with 100% modulus of 9 psi, while the elastic spine is made of Dragon Skin 10, with 100% modulus of 27 psi, such that the material hardness ratio corresponding to Young’s Modulus ratio of 1:3 can be achieved. A 90-mm long high-birefringence optical fiber with birefringence of 6.33×10−4 is embedded into the elastic spine that is fabricated by filling a 3-mm diameter cylindrical mold with Dragon skin 10. Once the elastic spine is cured, it is inserted to the center of the pneumatic channel mold (red in Fig. 2(c)). The mixture of Ecoflex 00-10 and 00-30 is used to fill the soft spiral gripper body mold. The soft spiral gripper is ready to be de-molded and tested once it is cured at room temperature for 3 hours.

In our experiment, a high-birefringence bow-tie fiber (F-HB 1500, Newport, USA) is used as the embedded sensor. Sagnac loop is formed outside of the soft spiral gripper to convert the detected twining angle into amplitude and wavelength shift information for measurement, as shown in Fig. 6. The pneumatic control system is the same as the one used in our previous work [9]. A broadband light source and an optical spectrum analyzer (OSA) (AP2040A, APEX Technologies) are used to observe the spectral characteristic of the Sagnac loop. A 90-mm long high-birefringence optical fiber with 1-m single mode fiber (SMF) and a polarization controller (PC) are connected at the right side of the optical coupler to form the Sagnac loop. When the soft spiral gripper is actuated, the embedded HiBi fiber is twisted and the birefringence of the fiber is varied slightly. The Sagnac loop converts the phase difference between the two counter propagating light into amplitude information via interference [24,25], resulting in a periodic cosine function across wavelength – referring to the optical comb. Therefore, the change in birefringence results in a change in the comb spacing (Δλ) of the optical interference spectrum based on the followed equation:

$$\Delta \lambda = \frac{{{\lambda ^2}}}{{\beta L}}$$
where β and L are the birefringence and length of the HiBi fiber, and λ is the wavelength range of the broadband light source. Since the change in comb spacing is small, a shift in the comb position is observed instead when the wavelength range of interest is small.

 figure: Fig. 6.

Fig. 6. Experimental setup for the embedded HiBi fiber optic sensor in the soft spiral gripper. SMF: single mode fiber; PC: polarization controller.

Download Full Size | PPT Slide | PDF

4. Results and discussion

The transmission notch of the comb is used as the reference to measure the amount of comb shift during twining (see the spiral gripper actuation video in Visualization 1). The optical transmission spectrum of the HiBi fiber at various twining angle is measured as shown in Fig. 7(a). A 16.66-nm wavelength shift is observed when the twining angle of the soft spiral gripper is increased from 0° to 540°. Then the relationship between the twining angle and the wavelength shift of the Sagnac loop spectrum is measured as shown by the blue data points in Fig. 7(b). A first order fitting line with a slope of 0.03nm/° is resulted and can be used to represent the twining sensitivity of the HiBi fiber sensor. The experiment is repeated for five times for measuring the wavelength shift and power change due to the change in twining angle. The deviations of the measured values are plotted as error bars. Small error bars is observed, which proves that both the spiral gripper and the embedded HiBi fiber optic sensor have high repeatability. The comb spectrum returns to the original spectral position every time after the soft spiral gripper is fully deflated, proofing that there is no delamination between the HiBi fiber sensor and the elastic spine in the soft spiral gripper, resulting in high sensing accuracy and repeatability.

 figure: Fig. 7.

Fig. 7. (a) Interfered optical spectra of the embedded HiBi fiber sensor in Sagnac configuration. (b) Effect of twining angle on the HiBi fiber optic sensor embedded in the spiral gripper - wavelength shift (blue) and power change (orange).

Download Full Size | PPT Slide | PDF

To enable real-time monitoring of the soft spiral gripper, optical power measurement is used instead of spectral measurement. A laser diode at 1545.363 nm and an optical power meter are used for power measurement. The laser wavelength is chosen to align with the transmission peak of the Sagnac loop spectrum at its original state (0° twining angle), such that the least power loss is resulted initially. As the soft spiral gripper is actuated, twining motion is observed and the transmission spectrum of the Sagnac loop shifts to the longer wavelength, resulting in a decrease in optical power at the laser wavelength. The measured power change is plotted in Fig. 7 in red when the soft spiral gripper is twining from 0 to 540°. It is shown that the optical power reduces as the twining angle increases and the power changing pattern follows closely to the Sagnac loop transmission spectrum. Again, small error bars (shown in pink) is obtained that proves that no delamination occurred and a highly repeatable twining plant-inspired soft spiral gripper with embedded sensor has been achieved.

Next, we studied the ability of the soft robotic spiral gripper to securely hold a target object with various diameters, and the ability for the HiBi fiber optic sensor to monitor the twining process, to identify the diameter of the target object, and detect any undesired external perturbations. A video of the spiral gripper gripping an object with 1-mm diameter can be found in Visualization 2. A laser diode at 1545.363 nm is used for monitoring the power change due to wavelength shift of the comb, and a LabView controlled optical power meter sampling at 2 Hz is used for real-time monitoring and data collection. Figure 8 shows the measured power change at the laser wavelength as the soft spiral gripper is performing various tasks and experiencing external perturbations.

 figure: Fig. 8.

Fig. 8. Real-time monitoring of the optical power change when the spiral gripper is performing various tasks and experiencing external perturbations.

Download Full Size | PPT Slide | PDF

Initially, the soft spiral gripper is at its original state without actuation. The measured optical power at the original state serves as the reference power, indicated by the red dash line at the top of Fig. 8. Next, the soft spiral gripper is actuated but without gripping any object. The onset of actuation is indicated by a small increase in optical power (blue circle), which is due to the initial pressure build up in the gripper before twining that squeezes the sensor. The squeeze from the cross plane induces a phase change of the HiBi fiber, which results in an increase in comb intensity.

Once the soft spiral gripper starts twining, optical power decreases continuously as the gripper is completing its 540° twining under a 0.67 MPa (i.e. 97psi) pneumatic pressure. A total power change of -11.48 dB is resulted and no further power change is observed as the gripper is fixed at its 540° twining point. Then, the gripper is deactuated (deflated) and resumes to its original state. Next, the spiral gripper is actuated again at 0.67 MPa to hold various cylindrical target objects using a 540° twining, including a 1-mm paper clip, a 4-mm paintbrush, and an 8-mm pencil. Once the soft spiral gripper reaches the 540° twining point, a -14.59 dB, -18.43 dB, and -23.21 dB change in power is observed for all the three cylindrical objects with diameters of 1-mm, 4-mm, and 8-mm, respectively. The result shows that the embedded HiBi fiber optic sensor is sensitive enough to identify the presence of an object as small as 1 mm in diameter. When the gripper is securely twining on the 4-mm paintbrush, an external force is applied to the brush in attempting to pull the paintbrush away. The HiBi fiber optic sensor captured this event and indicated with a rapid fluctuation in optical power change. It is observed that the smallest object diameter the spiral gripper can hold is 1 mm which is determined by the diameter of the hollow area of the actuated spiral gripper, while the largest diameter is 8 mm which is determined by how far does the spiral gripper twin around the object. Furthermore, a maximum of 60 g can be hold by the gripper before the object starts sliding down from the spiral gripper, the exact weight the spiral gripper can hold also depends on the texture of the object, i.e. friction between the spiral gripper and the target object.

5. Conclusion

In this work, we designed and optimized a twining plant inspired single-channel pneumatic soft spiral gripper with embedded HiBi fiber optic sensor for monitoring the twining motion, providing target object characteristics (capable of identifying objects as small as 1-mm in diameter), and detecting undesired external perturbation. The soft spiral gripper is capable of operating in a confined area and providing a 540° twining to securely hold onto an object. The HiBi fiber optic sensor is embedded in the elastic spine to prevent delamination during twining and offers a twining angle sensitivity of 0.03nm/°. Overall, the soft spiral gripper shows significant effectiveness of gripping object, great repeatability, high twining sensing accuracy and precise external perturbation detection. The unique single-channel pneumatic spiral gripper together with the embedded fiber optic sensor forms an essential building block in soft robotics to perform twining and twisting motions.

Disclosures

The authors declare no conflicts of interest.

References

1. F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011). [CrossRef]  

2. S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014). [CrossRef]  

3. S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015). [CrossRef]  

4. D. Ratna and J. Karger-Kocsis, “Recent advances in shape memory polymers and composites: a review,” J. Mater. Sci. 43(1), 254–269 (2008). [CrossRef]  

5. R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013). [CrossRef]  

6. C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012). [CrossRef]  

7. Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018). [CrossRef]  

8. Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015). [CrossRef]  

9. M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020). [CrossRef]  

10. R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018). [CrossRef]  

11. L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018). [CrossRef]  

12. H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016). [CrossRef]  

13. C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011). [CrossRef]  

14. J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016). [CrossRef]  

15. B. Huang and X. Shu, “Ultra-compact strain- and temperature-insensitive torsion sensor based on a line-by-line inscribed phase-shifted FBG,” Opt. Express 24(16), 17670–17679 (2016). [CrossRef]  

16. Y. P. Wang, J. P. Chen, and Y. J. Rao, “Torsion characteristics of long-period fiber gratings induced by high-frequency CO2 laser pulses,” J. Opt. Soc. Am. B 22(6), 1167–1172 (2005). [CrossRef]  

17. L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

18. A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020). [CrossRef]  

19. A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020). [CrossRef]  

20. Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014). [CrossRef]  

21. S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020). [CrossRef]  

22. J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

23. P. Boonvisut and M. C. Cavusoglu, “Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data,” IEEE/ASME Trans. Mechatron. 18(5), 1602–1611 (2013). [CrossRef]  

24. O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007). [CrossRef]  

25. R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019). [CrossRef]  

References

  • View by:

  1. F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
    [Crossref]
  2. S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
    [Crossref]
  3. S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
    [Crossref]
  4. D. Ratna and J. Karger-Kocsis, “Recent advances in shape memory polymers and composites: a review,” J. Mater. Sci. 43(1), 254–269 (2008).
    [Crossref]
  5. R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
    [Crossref]
  6. C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
    [Crossref]
  7. Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
    [Crossref]
  8. Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
    [Crossref]
  9. M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
    [Crossref]
  10. R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
    [Crossref]
  11. L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
    [Crossref]
  12. H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016).
    [Crossref]
  13. C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011).
    [Crossref]
  14. J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
    [Crossref]
  15. B. Huang and X. Shu, “Ultra-compact strain- and temperature-insensitive torsion sensor based on a line-by-line inscribed phase-shifted FBG,” Opt. Express 24(16), 17670–17679 (2016).
    [Crossref]
  16. Y. P. Wang, J. P. Chen, and Y. J. Rao, “Torsion characteristics of long-period fiber gratings induced by high-frequency CO2 laser pulses,” J. Opt. Soc. Am. B 22(6), 1167–1172 (2005).
    [Crossref]
  17. L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).
  18. A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
    [Crossref]
  19. A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
    [Crossref]
  20. Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
    [Crossref]
  21. S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
    [Crossref]
  22. J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).
  23. P. Boonvisut and M. C. Cavusoglu, “Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data,” IEEE/ASME Trans. Mechatron. 18(5), 1602–1611 (2013).
    [Crossref]
  24. O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007).
    [Crossref]
  25. R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
    [Crossref]

2020 (4)

M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
[Crossref]

A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
[Crossref]

A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
[Crossref]

S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
[Crossref]

2019 (1)

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

2018 (3)

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
[Crossref]

2016 (3)

H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016).
[Crossref]

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

B. Huang and X. Shu, “Ultra-compact strain- and temperature-insensitive torsion sensor based on a line-by-line inscribed phase-shifted FBG,” Opt. Express 24(16), 17670–17679 (2016).
[Crossref]

2015 (2)

Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
[Crossref]

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

2014 (2)

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

2013 (2)

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

P. Boonvisut and M. C. Cavusoglu, “Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data,” IEEE/ASME Trans. Mechatron. 18(5), 1602–1611 (2013).
[Crossref]

2012 (1)

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

2011 (2)

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011).
[Crossref]

2008 (1)

D. Ratna and J. Karger-Kocsis, “Recent advances in shape memory polymers and composites: a review,” J. Mater. Sci. 43(1), 254–269 (2008).
[Crossref]

2007 (1)

O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007).
[Crossref]

2005 (1)

Álvarez-Tamayo, R. I.

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Avellar, L.

A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
[Crossref]

Bai, Y.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Baptista, J. M. T.

O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007).
[Crossref]

Barcelata-Pinzón, A.

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Bauer, S.

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

Bauer-Gogonea, S.

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

Boonvisut, P.

P. Boonvisut and M. C. Cavusoglu, “Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data,” IEEE/ASME Trans. Mechatron. 18(5), 1602–1611 (2013).
[Crossref]

Branch, J. L.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

Campos, V.

A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
[Crossref]

Cavusoglu, M. C.

P. Boonvisut and M. C. Cavusoglu, “Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data,” IEEE/ASME Trans. Mechatron. 18(5), 1602–1611 (2013).
[Crossref]

Chen, J. P.

Chen, R.

J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

Chen, X.

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

Chen, Y.

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

Chung, H.-J.

S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
[Crossref]

Cianchetti, M.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Cleary, J.

Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
[Crossref]

Dario, P.

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Durán-Sánchez, M.

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Elsayed, Y.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Fang, W.

J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

Fish, C. R.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

Fok, M. P.

M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
[Crossref]

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

Follador, M.

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Frazao, O.

O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007).
[Crossref]

Frizera, A.

A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
[Crossref]

A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
[Crossref]

Ge, J.

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

Geng, T.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Graz, I.

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

Grosskopf, A. K.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Hao, M.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Huang, B.

Ibarra-Escamilla, B.

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Ilievski, F.

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

Islam, S.

S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
[Crossref]

James, A. E.

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

Jin, L.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

Kaltenbrunner, M.

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

Karger-Kocsis, J.

D. Ratna and J. Karger-Kocsis, “Recent advances in shape memory polymers and composites: a review,” J. Mater. Sci. 43(1), 254–269 (2008).
[Crossref]

Keplinger, C.

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

Kim, C. I. L.

S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
[Crossref]

Kramer, R.

C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011).
[Crossref]

Kuzin, E. A.

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Kwok, K. W.

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

Laschi, C.

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Leal-Junior, A.

A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
[Crossref]

A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
[Crossref]

Lekakou, C.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Lewis, J. A.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Li, C.

Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
[Crossref]

Li, L.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Li, S.

H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016).
[Crossref]

Li, T.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Li, Z.

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

Liang, H. Y.

J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

Lin, G.

Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
[Crossref]

Lin, M. Y.

J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

Liu, L.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Liu, N.

L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

Liu, Q.

M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
[Crossref]

Majidi, C.

C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011).
[Crossref]

Margheri, L.

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Marques, C.

A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
[Crossref]

A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
[Crossref]

Martinez, R. V.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

Mazzeo, A. D.

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

Mazzolai, B.

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Menciassi, A.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Meng, M. Q. H.

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

Naqawe, H. S.

M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
[Crossref]

Nunes, R. M.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

O’ Brien, K.

H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016).
[Crossref]

Peng, Z.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Prieto-Cortés, P.

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Ranzani, T.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Rao, Y. J.

Ratna, D.

D. Ratna and J. Karger-Kocsis, “Recent advances in shape memory polymers and composites: a review,” J. Mater. Sci. 43(1), 254–269 (2008).
[Crossref]

Ren, H. L.

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

Saaj, C. M.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Santos, J. L.

O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007).
[Crossref]

Schwodiauer, R.

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

She, Y.

Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
[Crossref]

Shepherd, R. F.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

Shu, X.

Song, S.

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

Su, H. J.

Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
[Crossref]

Sun, F.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Suo, Z.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

Tang, Y.

Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
[Crossref]

Truby, R. L.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Uzel, S. G. M.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Vincensi, A.

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Vogt, D. M.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Wang, J. J.

J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

Wang, S.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Wang, X. Q.

L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

Wang, Y. P.

Wehner, M.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Whitesides, G. M.

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

Wood, R. J.

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011).
[Crossref]

Xiang, H.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Xiong, Y.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Xu, J.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Xu, L.

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

Yang, M.

M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
[Crossref]

Yin, J.

Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
[Crossref]

Yu, H. Y.

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

Zhalmuratova, D.

S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
[Crossref]

Zhang, Q.

Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
[Crossref]

Zhang, T.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Zhao, H.

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016).
[Crossref]

Adv. Mater. (3)

S. Bauer, S. Bauer-Gogonea, I. Graz, M. Kaltenbrunner, C. Keplinger, and R. Schwodiauer, “25th anniversary article: A soft future: from robots and sensor skin to energy harvesters,” Adv. Mater. 26(1), 149–162 (2014).
[Crossref]

R. V. Martinez, J. L. Branch, C. R. Fish, L. Jin, R. F. Shepherd, R. M. Nunes, Z. Suo, and G. M. Whitesides, “Robotic tentacles with three-dimensional mobility based on flexible elastomers,” Adv. Mater. 25(2), 205–212 (2013).
[Crossref]

R. L. Truby, M. Wehner, A. K. Grosskopf, D. M. Vogt, S. G. M. Uzel, R. J. Wood, and J. A. Lewis, “Soft Somatosensitive Actuators via Embedded 3D Printing,” Adv. Mater. 30(15), 1706383 (2018).
[Crossref]

Adv. Robotics (1)

C. Laschi, M. Cianchetti, B. Mazzolai, L. Margheri, M. Follador, and P. Dario, “Soft Robot Arm Inspired by the Octopus,” Adv. Robotics 26(7), 709–727 (2012).
[Crossref]

Adv. Sci. (1)

L. Li, H. Xiang, Y. Xiong, H. Zhao, Y. Bai, S. Wang, F. Sun, M. Hao, L. Liu, T. Li, Z. Peng, J. Xu, and T. Zhang, “Ultrastretchable Fiber Sensor with High Sensitivity in Whole Workable Range for Wearable Electronics and Implantable Medicine,” Adv. Sci. 5(9), 1800558 (2018).
[Crossref]

Angew. Chem. Int. Ed. (1)

F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, and G. M. Whitesides, “Soft robotics for chemists,” Angew. Chem. Int. Ed. 50(8), 1890–1895 (2011).
[Crossref]

IEEE Photonics Technol. Lett. (1)

J. Ge, A. E. James, L. Xu, Y. Chen, K. W. Kwok, and M. P. Fok, “Bidirectional Soft Silicone Curvature Sensor Based on Off-Centered Embedded Fiber Bragg Grating,” IEEE Photonics Technol. Lett. 28(20), 2237–2240 (2016).
[Crossref]

IEEE Sens. J. (1)

S. Song, Z. Li, M. Q. H. Meng, H. Y. Yu, and H. L. Ren, “Real-Time Shape Estimation for Wire-Driven Flexible Robots With Multiple Bending Sections Based on Quadratic Bezier Curves,” IEEE Sens. J. 15(11), 6326–6334 (2015).
[Crossref]

IEEE/ASME Trans. Mechatron. (1)

P. Boonvisut and M. C. Cavusoglu, “Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data,” IEEE/ASME Trans. Mechatron. 18(5), 1602–1611 (2013).
[Crossref]

Int. J. Solids Struct. (1)

S. Islam, D. Zhalmuratova, H.-J. Chung, and C. I. L. Kim, “A model for hyperelastic materials reinforced with fibers resistance to extension and flexure,” Int. J. Solids Struct. 193-194, 418–433 (2020).
[Crossref]

J. Mater. Sci. (1)

D. Ratna and J. Karger-Kocsis, “Recent advances in shape memory polymers and composites: a review,” J. Mater. Sci. 43(1), 254–269 (2008).
[Crossref]

J. Mechanisms Robot. (1)

Y. She, C. Li, J. Cleary, and H. J. Su, “Design and Fabrication of a Soft Robotic Hand With Embedded Actuators and Sensors,” J. Mechanisms Robot. 7(2), 021007 (2015).
[Crossref]

J. Opt. Soc. Am. B (1)

Mater. Lett. (1)

A. Leal-Junior, V. Campos, A. Frizera, and C. Marques, “Low-cost and high-resolution pressure sensors using highly stretchable polymer optical fibers,” Mater. Lett. 271, 127810 (2020).
[Crossref]

Opt. Express (1)

Photonic Sens. (1)

R. I. Álvarez-Tamayo, P. Prieto-Cortés, M. Durán-Sánchez, B. Ibarra-Escamilla, A. Barcelata-Pinzón, and E. A. Kuzin, “Laser Wavelength Estimation Method Based on a High-Birefringence Fiber Loop Mirror,” Photonic Sens. 9(1), 89–96 (2019).
[Crossref]

Sci. Rep. (1)

A. Leal-Junior, L. Avellar, A. Frizera, and C. Marques, “Smart textiles for multimodal wearable sensing using highly stretchable multiplexed optical fiber system,” Sci. Rep. 10(1), 13867 (2020).
[Crossref]

Sci. Robot. (3)

Y. Elsayed, A. Vincensi, C. Lekakou, T. Geng, C. M. Saaj, T. Ranzani, M. Cianchetti, and A. Menciassi, “Finite Element Analysis and Design Optimization of a Pneumatically Actuating Silicone Module for Robotic Surgery Applications,” Sci. Robot. 1(4), 255–262 (2014).
[Crossref]

Y. Tang, Q. Zhang, G. Lin, and J. Yin, “Switchable Adhesion Actuator for Amphibious Climbing Soft Robot,” Sci. Robot. 5(5), 592–600 (2018).
[Crossref]

H. Zhao, K. O’ Brien, and S. Li, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Sci. Robot. 1(1), eaai7529 (2016).
[Crossref]

Sensors (2)

M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors 20(5), 1312 (2020).
[Crossref]

O. Frazao, J. M. T. Baptista, and J. L. Santos, “Recent Advances in High-Birefringence Fiber Loop Mirror Sensors,” Sensors 7(11), 2970–2983 (2007).
[Crossref]

Smart Mater. Struct. (1)

C. Majidi, R. Kramer, and R. J. Wood, “A non-differential elastomer curvature sensor for softer-than-skin electronics,” Smart Mater. Struct. 20(10), 105017 (2011).
[Crossref]

Other (2)

L. Xu, N. Liu, J. Ge, X. Q. Wang, and M. P. Fok, “Stretchable multi-function fiber sensor for tension, bending and torsion sensing,” 2018 Optical Fiber Communications Conference and Exposition (OFC) (2018).

J. J. Wang, M. Y. Lin, H. Y. Liang, R. Chen, and W. Fang, “Piezoresistive Nanocomposite Rubber Elastomer for Stretchable Mems Sensor,” Proc Ieee Micr Elect, 550–553 (2016).

Supplementary Material (2)

NameDescription
Visualization 1       The spiral gripper is actuated without gripping any objects.
Visualization 2       The spiral gripper is actuated to grip a 1-mm paperclip, the optical power change is monitored and displayed on the same screen.

Cited By

Optica participates in Crossref's Cited-By Linking service. Citing articles from Optica Publishing Group journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (8)

Fig. 1.
Fig. 1. (a) Illustration of the twining motion in twining plant; (b) Soft spiral gripper before actuation; (c) Actuated soft spiral gripper holding a flower.
Fig. 2.
Fig. 2. (a) Top view of the soft spiral gripper (b) 3D view of the soft spiral gripper (c) 3D-printed molds for fabricating the soft spiral gripper.
Fig. 3.
Fig. 3. Relationship between azimuthal angle of the helical pneumatic channel and maximum twining angle of the soft spiral gripper with Young’s modulus (YM) ratio between the gripper body and the elastic spine of 1:1, 1:2, 1:3, and 1:4.
Fig. 4.
Fig. 4. Hollow area diameter of the actuated soft spiral gripper changes with Young’s modulus ratio between spiral gripper body and the elastic spine. (a) 1:1 ratio result in hollow area with a 0.8-mm diameter; (b) 1:2 ratio result in hollow area with a 0.9-mm diameter; (c) 1:3 ratio result in hollow area with a 1.0-mm diameter hollow area; (d)1:4 ratio result in hollow area with a 1.3-mm diameter hollow area.
Fig. 5.
Fig. 5. Relationship between the applied pneumatic pressure and the resultant twining angle under different Young’s modulus ratio.
Fig. 6.
Fig. 6. Experimental setup for the embedded HiBi fiber optic sensor in the soft spiral gripper. SMF: single mode fiber; PC: polarization controller.
Fig. 7.
Fig. 7. (a) Interfered optical spectra of the embedded HiBi fiber sensor in Sagnac configuration. (b) Effect of twining angle on the HiBi fiber optic sensor embedded in the spiral gripper - wavelength shift (blue) and power change (orange).
Fig. 8.
Fig. 8. Real-time monitoring of the optical power change when the spiral gripper is performing various tasks and experiencing external perturbations.

Tables (1)

Tables Icon

Table 1. Comparison of different material ratio under the 450° azimuthal angle model.

Equations (1)

Equations on this page are rendered with MathJax. Learn more.

Δ λ = λ 2 β L

Metrics