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A Locust-Inspired Robot Capable of Continuous Crawl–Jump–Gliding Locomotion With Optimized Transitional Control

Yi Xu, Peng Liang, Qijie Zhou, Qi Li, Qing Shi

Year
2024
Citations
19

Abstract

Locusts have various motion modes among which they continuously switch in terrestrial and aerial domains, hence achieving high environmental adaptability. Several robots have been developed to mimic the jump–gliding locomotion of locusts, but their mobility and transitional stability are limited because of structural and control limitations at a small scale. In this article, we develop a small-scale locust-inspired robot (LocustBot) that can not only jump and glide but also crawl. We propose a coordinately actuated mechanism that allows LocustBot to perform jump–gliding with few actuators. To achieve the stable and long-distance moving, a reinforcement-learning-based optimized control is used to generate then track the robot's position and orientation from take-off to landing. The jump–gliding distance of LocustBot reaches 5.39 m, revealing a high-energy utilization efficiency of the mobile strategy, which combines the spring-driven jumping with the propeller-driven gliding. Remarkably, without a high platform, the robot can still achieve a far moving range by continuous crawl–jump–gliding on horizontal planes and, thus, outperforms the state-of-art jump–gliding robots.

Keywords

LocustRobotRobot locomotionJumpControl theory (sociology)Computer scienceArtificial intelligenceRobot controlControl engineeringControl (management)

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