TY - GEN
T1 - Soft robotic fingers with embedded ionogel sensors and discrete actuation modes for somatosensitive manipulation
AU - Truby, Ryan L.
AU - Katzschmann, Robert K.
AU - Lewis, Jennifer A.
AU - Rus, Daniela
N1 - Funding Information:
ACKNOWLEDGMENT R.L.T. is supported by the Schmidt Science Fellows program, in partnership with the Rhodes Trust. J.A.L. is supported by the National Science Foundation (NSF) through the Harvard MRSEC (DMR-1420570) and the GETTYLAB. The authors gratefully acknowledge additional support through the NSF EFRI (1830901).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/24
Y1 - 2019/5/24
N2 - Soft robotic grippers enable gentle, adaptive, and bioinspired manipulation that is simply not possible using traditional rigid robots. However, it has remained challenging to create multi-degree-of-freedom soft actuators with appropriate sensory capabilities for soft manipulators requiring greater dexterity and closed-loop control. In this work, we use embedded 3D printing to produce soft robotic fingers with discrete actuation modes and integrated ionogel soft sensors that provide proprioceptive and tactile sensing corresponding to each degree of freedom. With new readout electronics that streamline the measurement of sensor resistance, we evaluate the fingers' sensory feedback through free and blocked displacement experiments. We integrate three of our sensorized fingers together to create a soft manipulator with different grasping poses. Finally, we showcase the importance of the fingers' discrete actuation modes and integrated sensors via a closed-loop grasping study. Our methods demonstrate an enabling manufacturing platform that can be adapted to create other soft multi-DOF manipulators requiring somatosensory feedback for a variety of closed-loop and machine learning-based control algorithms.
AB - Soft robotic grippers enable gentle, adaptive, and bioinspired manipulation that is simply not possible using traditional rigid robots. However, it has remained challenging to create multi-degree-of-freedom soft actuators with appropriate sensory capabilities for soft manipulators requiring greater dexterity and closed-loop control. In this work, we use embedded 3D printing to produce soft robotic fingers with discrete actuation modes and integrated ionogel soft sensors that provide proprioceptive and tactile sensing corresponding to each degree of freedom. With new readout electronics that streamline the measurement of sensor resistance, we evaluate the fingers' sensory feedback through free and blocked displacement experiments. We integrate three of our sensorized fingers together to create a soft manipulator with different grasping poses. Finally, we showcase the importance of the fingers' discrete actuation modes and integrated sensors via a closed-loop grasping study. Our methods demonstrate an enabling manufacturing platform that can be adapted to create other soft multi-DOF manipulators requiring somatosensory feedback for a variety of closed-loop and machine learning-based control algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85067127458&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067127458&partnerID=8YFLogxK
U2 - 10.1109/ROBOSOFT.2019.8722722
DO - 10.1109/ROBOSOFT.2019.8722722
M3 - Conference contribution
AN - SCOPUS:85067127458
T3 - RoboSoft 2019 - 2019 IEEE International Conference on Soft Robotics
SP - 322
EP - 329
BT - RoboSoft 2019 - 2019 IEEE International Conference on Soft Robotics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Soft Robotics, RoboSoft 2019
Y2 - 14 April 2019 through 18 April 2019
ER -