no code implementations • 26 May 2022 • Lingfeng Tao, Jiucai Zhang, Xiaoli Zhang
Dexterous manipulation tasks usually have multiple objectives, and the priorities of these objectives may vary at different phases of a manipulation task.
no code implementations • 26 May 2022 • Yunsik Jung, Lingfeng Tao, Michael Bowman, Jiucai Zhang, Xiaoli Zhang
In this work, we develop a novel Physics-Guided Deep Reinforcement Learning with a Hierarchical Reward Mechanism to improve learning efficiency and generalizability for learning-based autonomous grasping.
no code implementations • 19 Dec 2020 • Lingfeng Tao, Michael Bowman, Jiucai Zhang, Xiaoli Zhang
In human-robot cooperation, the robot cooperates with humans to accomplish the task together.
no code implementations • 7 Mar 2020 • Lingfeng Tao, Michael Bowman, Xu Zhou, Jiucai Zhang, Xiaoli Zhang
Enabling robots to provide effective assistance yet still accommodating the operator's commands for telemanipulation of an object is very challenging because robot's assistive action is not always intuitive for human operators and human behaviors and preferences are sometimes ambiguous for the robot to interpret.
no code implementations • 1 Mar 2020 • Lingfeng Tao, Michael Bowman, Jiucai Zhang, Xiaoli Zhang
Applying Deep Reinforcement Learning (DRL) to Human-Robot Cooperation (HRC) in dynamic control problems is promising yet challenging as the robot needs to learn the dynamics of the controlled system and dynamics of the human partner.