Towards Biosignals-Free Autonomous Prosthetic Hand Control via Imitation Learning

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The system autonomously grasps and releases objects of various shapes, enhancing usability for users.
Imitation learning achieved high success rates, demonstrating effectiveness over different weights and user variations.
By relying on a camera rather than myoelectric signals, the prosthetic becomes easier to control.
The teleoperation system collects demonstration data from human users to train the model, facilitating adaptability.

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This system enables autonomous control of a prosthetic hand using imitation learning, suggesting reduced mental effort for users.

Shi et al. (2025) studied this question.

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