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Hybrid Compliant Musculoskeletal System for Fast Actuation in Robots.

Pieter WiersingaAidan SleavinBart BoomThijs MasmeijerSpencer FlintEd Habtour
Published in: Micromachines (2022)
A nature-inspired musculoskeletal system is designed and developed to examine the principle of nonlinear elastic energy storage-release for robotic applications. The musculoskeletal system architecture consists of elastically rigid segments and hyperelastic soft materials to emulate rigid-soft interactions in limbless vertebrates. The objectives are to (i) improve the energy efficiency of actuation beyond that of current pure soft actuators while (ii) producing a high range of motion similar to that of soft robots but with structural stability. This paper proposes a musculoskeletal design that takes advantage of structural segmentation to increase the system's degrees of freedom, which enhances the range of motion. Our findings show that rigid-soft interactions provide a remarkable increase in energy storage and release and, thus, an increase in the undulation speed. The energy efficiency achieved is approximately 68% for bending the musculoskeletal system from the straight configuration, compared to 2.5-30% efficiency in purely soft actuators. The hybrid compliance of the musculoskeletal system under investigation shows promise for alleviating the need for actuators at each joint in a robot.
Keyphrases
  • deep learning
  • convolutional neural network
  • artificial intelligence
  • big data
  • high resolution