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Scalable Simulation and Demonstration of Jumping Piezoelectric 2-D Soft Robots

Authors :
Zheng, Zhiwu
Kumar, Prakhar
Chen, Yenan
Cheng, Hsin
Wagner, Sigurd
Chen, Minjie
Verma, Naveen
Sturm, James C.
Source :
2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 5199-5204
Publication Year :
2022

Abstract

Soft robots have drawn great interest due to their ability to take on a rich range of shapes and motions, compared to traditional rigid robots. However, the motions, and underlying statics and dynamics, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we demonstrate a five-actuator soft robot capable of complex motions and develop a scalable simulation framework that reliably predicts robot motions. The simulation framework is validated by comparing its predictions to experimental results, based on a robot constructed from piezoelectric layers bonded to a steel-foil substrate. The simulation framework exploits the physics engine PyBullet, and employs discrete rigid-link elements connected by motors to model the actuators. We perform static and AC analyses to validate a single-unit actuator cantilever setup and observe close agreement between simulation and experiments for both the cases. The analyses are extended to the five-actuator robot, where simulations accurately predict the static and AC robot motions, including shapes for applied DC voltage inputs, nearly-static "inchworm" motion, and jumping (in vertical as well as vertical and horizontal directions). These motions exhibit complex non-linear behavior, with forward robot motion reaching ~1 cm/s. Our open-source code can be found at: https://github.com/zhiwuz/sfers.<br />Comment: Accepted to the International Conference on Robotics and Automation (ICRA) 2022. Video: https://youtu.be/nHcH3V7rCrk

Details

Database :
arXiv
Journal :
2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 5199-5204
Publication Type :
Report
Accession number :
edsarx.2202.13521
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/ICRA46639.2022.9811927