9 citations · 39 across the 16 of their papers we have counts for
6 papers · 1 filter
Forming Real-World Human-Robot Cooperation for Tasks With General Goal
Lingfeng Tao, Michael Bowman, Jiucai Zhang +1
In human-robot cooperation, the robot cooperates with humans to accomplish the task together. Existing approaches assume the human has a specific goal during the cooperation, and t…
Robust Robot-assisted Tele-grasping Through Intent-Uncertainty-Aware Planning
Michael Bowman, Songpo Li, Xiaoli Zhang
In teleoperation, research has mainly focused on target approaching, where we deal with the more challenging object manipulation task by advancing the shared control technique. App…
A General Arbitration Model for Robust Human-Robot Shared Control with Multi-Source Uncertainty Modeling
Songpo Li, Michael Bowman, Xiaoli Zhang
Shared control in teleoperation leverages both human and robot's strengths and has demonstrated great advantages of reducing the difficulties in teleoperating a robot and increasin…
Learn and Transfer Knowledge of Preferred Assistance Strategies in Semi-autonomous Telemanipulation
Lingfeng Tao, Michael Bowman, Xu Zhou +2
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 acti…
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration
Sen Liu, Branden B. Kappes, Behnam Amin-ahmadi +3
Machine learning (ML) is shown to predict new alloys and their performances in a high dimensional, multiple-target-property design space that considers chemistry, multi-step proces…
Learn Task First or Learn Human Partner First: A Hierarchical Task Decomposition Method for Human-Robot Cooperation
Lingfeng Tao, Michael Bowman, Jiucai Zhang +1
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…