A Study of Assistive Robotics in Simulation Environment
DOI:
https://doi.org/10.47611/jsrhs.v12i1.4183Keywords:
Assistive Robotic, Reinforcement Learning , Assistive Gym , OpenAI Gym , Physics Simulator ,PyBullet, RLlib , Healthcare ,Abstract
As the demand for caregiving increases, robots hold significant promise to provide improvements in the quality of life for millions worldwide. While previous research has provided baseline learning environments, this experiment investigates the adaptability of control policies in new environments more realistic to real world applications. Using Assistive Gym, an open source physics simulation framework for the study, the 6 commercial robots were trained with control policies, then in a customized bed/bathing environment with varying bed positions and multi robot reaching environment with cooperative reinforcement learning.
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