TY - GEN
T1 - A soft actuator with tunable mechanical configurations for object grasping based on sensory feedback
AU - Fang, Xi
AU - Liu, Zemin
AU - Hao, Yufei
AU - Yang, Hui
AU - Liu, Jiaqi
AU - Xie, Zhexin
AU - Wen, Li
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/24
Y1 - 2019/5/24
N2 - In this paper, we propose a soft actuator embedded with conductive liquid alloy (eGaIn) and Shape Memory Polymer (SMP). The conductive liquid alloy functions as bending sensor as well as pressure sensor. The three segments of the SMP layer can be heated optionally by applying 400mA current to different sections of the conductive silver fiber to achieve tunable stiffness, and enable the soft actuator with variable degree-of-freedom (DoF) configurations. Through real-time feedback of the bending sensor that has been calibrated, we realized proprioception of all mechanical configurations of the soft actuator under free load. We also achieved geometrical feature recognition of different objects while all segments of the actuator were softened. Finally, experimental verification of the prototype was conducted on a variety of objects in condition that the geometrical features were unknown. The results show improved enveloping and reliable grasping performance.
AB - In this paper, we propose a soft actuator embedded with conductive liquid alloy (eGaIn) and Shape Memory Polymer (SMP). The conductive liquid alloy functions as bending sensor as well as pressure sensor. The three segments of the SMP layer can be heated optionally by applying 400mA current to different sections of the conductive silver fiber to achieve tunable stiffness, and enable the soft actuator with variable degree-of-freedom (DoF) configurations. Through real-time feedback of the bending sensor that has been calibrated, we realized proprioception of all mechanical configurations of the soft actuator under free load. We also achieved geometrical feature recognition of different objects while all segments of the actuator were softened. Finally, experimental verification of the prototype was conducted on a variety of objects in condition that the geometrical features were unknown. The results show improved enveloping and reliable grasping performance.
UR - https://www.scopus.com/pages/publications/85067095045
U2 - 10.1109/ROBOSOFT.2019.8722761
DO - 10.1109/ROBOSOFT.2019.8722761
M3 - 会议稿件
AN - SCOPUS:85067095045
T3 - RoboSoft 2019 - 2019 IEEE International Conference on Soft Robotics
SP - 25
EP - 30
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 -