Journal
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
Volume -, Issue -, Pages 11775-11781Publisher
IEEE
DOI: 10.1109/ICRA48506.2021.9561420
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Funding
- National Science Foundation (NSF) [1637446, 2024247]
- Air Force Office of Scientific Research [FA2386-17-1-4658]
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [2024247] Funding Source: National Science Foundation
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This paper examines the dynamics simulator for vine robots, a type of soft growing robots, that is capable of capturing general behaviors and interactions with the environment in real time. The study successfully bridges the sim-to-real gap by developing methods for fitting model parameters based on video data, showing qualitative and quantitative agreement between simulated and real behaviors.
Simulating soft robots in cluttered environments remains an open problem due to the challenge of capturing complex dynamics and interactions with the environment. Furthermore, fast simulation is desired for quickly exploring robot behaviors in the context of motion planning. In this paper, we examine a particular class of inflated-beam soft growing robots called vine robots, and present a dynamics simulator that captures general behaviors, handles robot-object interactions, and runs faster than real time. The simulator framework uses a simplified multi-link, rigid-body model with contact constraints. To bridge the sim-to-real gap, we develop methods for fitting model parameters based on video data of a robot in motion and in contact with an environment. We provide examples of simulations, including several with lit parameters, to show the qualitative and quantitative agreement between simulated and real behaviors. Our work demonstrates the capabilities of this high-speed dynamics simulator and its potential for use in the control of soft robots.
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