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Conference Papers Year : 2021

Computational design of energy-efficient legged robots: Optimizing for size and actuators

Abstract

This paper presents a computational framework for the design of high-performance legged robotic systems. The framework relies on the concurrent optimization of hardware parameters and control trajectories to find the best robot design for a given task. In particular, we focus on energy efficiency, presenting novel electro-mechanical models to account for the losses of the actuators due to friction and Joule effects. Thanks to a bi-level optimization scheme, featuring a genetic algorithm in the outer loop, our framework can also optimize for the duration of the motion, the actuators, and the size of the robot. We present a novel approach to scale both the actuators and the robot structure in a way that ensures structural integrity by maintaining constant the normalized deflection of the links. We validated our approach by designing a two-joint monoped robot to execute a jumping task. Our results show that our framework can lead to remarkable energy savings (up to 60%) thanks to the concurrent optimization of robot size, motion duration, and actuators.
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Dates and versions

hal-02993624 , version 1 (23-11-2020)
hal-02993624 , version 2 (07-04-2021)

Identifiers

Cite

Gabriele Fadini, Thomas Flayols, Andrea del Prete, Nicolas Mansard, Philippe Souères. Computational design of energy-efficient legged robots: Optimizing for size and actuators. IEEE International Conference on Robotics and Automation (ICRA 2021), May 2021, Xian, China. ⟨10.1109/ICRA48506.2021.9560988⟩. ⟨hal-02993624v2⟩
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