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Found 4 papers, 2 papers with code
The utility of tactile force to autonomous learning of in-hand manipulation is task-dependent
Surprisingly, and contrary to recent work on manipulation, adding 1D force-sensing did not always improve learning rates compared to no sensing---likely due to whether or not normal force is relevant to the task.
Simple Kinematic Feedback Enhances Autonomous Learning in Bio-Inspired Tendon-Driven Systems
Error feedback is known to improve performance by correcting control signals in response to perturbations.
Autonomous Functional Locomotion in a Tendon-Driven Limb via Limited Experience
Robots will become ubiquitously useful only when they can use few attempts to teach themselves to perform different tasks, even with complex bodies and in dynamical environments.
Shapechanger: Environments for Transfer Learning
We present Shapechanger, a library for transfer reinforcement learning specifically designed for robotic tasks.
