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MANIPULATION

Self‐Sensing Artificial‐Muscle‐Empowered Humanlike Perception, Interaction, and Positioning

Houping Wu, Yufeng Wang, Zhengyan Wang, Yulian Peng, Hongbo Wang

Year
2024
Citations
9
Access
Open access

Abstract

Bioinspired soft and hybrid robots provide a promising solution to developing robots that can interact and collaborate with humans safely and effectively. Bellow‐like pneumatic artificial muscles can produce biological muscle‐like contraction with comparable response time and force output, but closed‐loop control has been a challenge without an effective length sensing solution. Herein, a self‐sensing artificial muscle (SSAM), which can sense its own length regardless of the external loadings and driving pressures, is proposed. Empowered by a seamlessly integrated mutual‐inductance‐based length sensor (MILS), the SSAM can sense its length change as small as 0.01 mm (0.012% of the initial liength 80 mm) in a wide range. The working principle of the MILS is analyzed theoretically to provide a design guideline. An SSAM‐based earthworm‐like locomotion robot is developed with the capability of knowing its real‐time body length change at different gaits. An artificial arm driven by one SSAM is also developed and demonstrated with humanlike capabilities of loading perception, interactive and responsive movements, and accurate positioning. This work provides a promising solution to develop muscle‐driven hybrid robotic systems with embodied intelligence for skilled manipulation and sophisticated human–machine interactions.

Keywords

Artificial musclePerceptionHuman–computer interactionComputer scienceArtificial intelligenceCommunicationPsychologyNeuroscience

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