ClothPPO: A Proximal Policy Optimization Enhancing Framework for Robotic Cloth Manipulation with Observation-Aligned Action Spaces

arXiv:2405.04549v1 Announce Type: new
Abstract: Vision-based robotic cloth unfolding has made great progress recently. However, prior works predominantly rely on value learning and have not fully explored policy-based techniques. Recently, the success of reinforcement learning on the large language model has shown that the policy gradient algorithm can enhance policy with huge action space. In this paper, we introduce ClothPPO, a framework that employs a policy gradient algorithm based on actor-critic architecture to enhance a pre-trained model with huge 10^6 …

abstract arxiv cs.ai cs.cv cs.ro framework however language language model large language large language model manipulation observation optimization policy prior progress reinforcement reinforcement learning robotic spaces success type value vision