TY - GEN
T1 - Spline-based modeling and control of soft robots
AU - Luo, Shuzhen
AU - Edmonds, Merrill
AU - Yi, Jingang
AU - Zhou, Xianlian
AU - Shen, Yantao
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - Soft robots demonstrate superior flexibility and maneuverability than traditional rigid robots in many emerging applications. However, it is challenging to have a general modeling and control methodology to deal with soft body dynamics and its interactions with environment. We present a spline-based modeling and control framework for soft robotic systems. The dynamic model is built on non-uniform rational Bsplines (NURBS) that captures material and physical properties of soft body, while preserving exact geometric dynamics with environmental interactions. Using the NURBS-based dynamic model, the robotic optimal control based on general predictive control is designed through coordination among the finite number of control points. Therefore, the infinite-dimensional motion of soft body can be realized by significantly reduced finite particle motion control. We demonstrate the performance of the modeling and motion control framework using the snakeinspired robot simulations and experiments.
AB - Soft robots demonstrate superior flexibility and maneuverability than traditional rigid robots in many emerging applications. However, it is challenging to have a general modeling and control methodology to deal with soft body dynamics and its interactions with environment. We present a spline-based modeling and control framework for soft robotic systems. The dynamic model is built on non-uniform rational Bsplines (NURBS) that captures material and physical properties of soft body, while preserving exact geometric dynamics with environmental interactions. Using the NURBS-based dynamic model, the robotic optimal control based on general predictive control is designed through coordination among the finite number of control points. Therefore, the infinite-dimensional motion of soft body can be realized by significantly reduced finite particle motion control. We demonstrate the performance of the modeling and motion control framework using the snakeinspired robot simulations and experiments.
UR - http://www.scopus.com/inward/record.url?scp=85090383551&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090383551&partnerID=8YFLogxK
U2 - 10.1109/AIM43001.2020.9158917
DO - 10.1109/AIM43001.2020.9158917
M3 - Conference contribution
AN - SCOPUS:85090383551
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 482
EP - 487
BT - 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2020
Y2 - 6 July 2020 through 9 July 2020
ER -