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This work introduces a novel 12-motor paired-cable actuation scheme to achieve rolling locomotion with a spherical tensegrity structure. Using a new point mass tensegrity dynamic formulation which we present, we utilize Model Predictive Control to generate optimal state-action trajectories for benchmark evaluation. In particular, locomotive performance is assessed based on the practical criteria of rolling speed, energy efficiency, and directional trajectory-tracking accuracy. Through simulation of 6-motor, 12-motor paired cable, and 24-motor fully-actuated policies, we demonstrate that the 12-motor schema is superior to the 6-motor policy in all benchmark categories, comparable to the 24-motor policy in rolling speed, and is over five times more energy efficient than the fully-actuated 24-motor configuration.
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Any-axis Tensegrity Rolling via Bootstrapped Learning and Symmetry Reduction
Tensegrity rovers incorporate design principles that give rise to many desirable properties, such as adaptability and robustness, while also creating challenges in terms of locomotion control. A recent milestone in this area combined reinforcement learning and optimal control to effect fixed-axis rolling of NASA’s 6-bar spherical tensegrity rover prototype, SUPERball, with use of 12 actuators. The new 24-actuator version of SUPERball presents the potential for greatly increased locomotive abilities, but at a drastic nominal increase in the size of the data-driven control problem. This paper is focused upon unlocking those abilities while crucially moderating data requirements by incorporating symmetry reduction into the controller design pipeline, along with other new considerations. Experiments in simulation and on the hardware prototype demonstrate the resulting capability for any-axis rolling on the 24-actuator version of SUPERball, such that it may utilize diverse ground-contact patterns to smoothly locomote in arbitrary directions.
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- PAR ID:
- 10145335
- Date Published:
- Journal Name:
- International Symposium on Experimental Robotics (ISER)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This work introduces a novel 12-motor paired-cable actuation scheme to achieve rolling locomotion with a spherical tensegrity structure. Using a new point mass tensegrity dynamic formulation which we present, we utilize Model Predictive Control to generate optimal state-action trajectories for benchmark evaluation. In particular, locomotive performance is assessed based on the practical criteria of rolling speed, energy efficiency, and directional trajectory-tracking accuracy. Through simulation of 6-motor, 12-motor paired-cable, and 24-motor fully-actuated policies, we demonstrate that the 12-motor schema is superior to the 6-motor policy in all benchmark categories, comparable to the 24-motor policy in rolling speed, and is over five times more energy efficient than the fully-actuated 24-motor configuration.more » « less
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