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Tracking Displacement of a Worm-Like Robot With Multiple Sensor Configurations

Mingyi Wang, Natasha Rouse, Kathryn A. Daltorio

发表年份
2023
引用次数
5

摘要

Worm-like robots that mimic the peristaltic locomotion of earthworms have high robustness to complex environments. These robots’ movements are driven by the deformation of the body, but this compliance in the body brings challenges for tracking and control. This work compares three sensing methods to track a worm-like robot’s displacement: the actuator forward modeling method (AFMM), the stretch and pressure sensor method (SPSM), and the inertial measurement unit method (IMUM). Each of these methods is compared against a true displacement determined by vision tracking. Based on experimental results, SPSM yields the lowest average error (underestimating the true value by 17% on average), AFMM is slightly higher (20% underestimation), and the IMU result has a comparatively large average error (77% overestimation). AFMM failed to track the robot’s backward slip, while both SPSM and IMUM showed the ability of slip detection.

关键词

RobotRobustness (evolution)Inertial measurement unitDisplacement (psychology)Tracking (education)Computer scienceComputer visionActuatorCrawlingPeristalsis

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