research
∙
08/23/2023
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning
The driving style of an Autonomous Vehicle (AV) refers to how it behaves...
share
research
∙
07/29/2023
Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning
Reinforcement learning (RL) for motion planning of multi-degree-of-freed...
research
∙
06/05/2023
Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous Driving
Reinforcement learning (RL) is an effective approach to motion planning ...
research
∙
04/12/2023
Exploiting Intrinsic Stochasticity of Real-Time Simulation to Facilitate Robust Reinforcement Learning for Robot Manipulation
Simulation is essential to reinforcement learning (RL) before implementa...
research
∙
04/12/2023
Exploiting Symmetry and Heuristic Demonstrations in Off-policy Reinforcement Learning for Robotic Manipulation
Reinforcement learning demonstrates significant potential in automatical...
research
∙
04/12/2023
Distributed Coverage Control of Constrained Constant-Speed Unicycle Multi-Agent Systems
This paper proposes a novel distributed coverage controller for a multi-...
research
∙
04/12/2023
Human-Robot Skill Transfer with Enhanced Compliance via Dynamic Movement Primitives
Finding an efficient way to adapt robot trajectory is a priority to impr...
research
∙
04/01/2023
Automated Formation Control Synthesis from Temporal Logic Specifications
In this paper, we propose a novel framework using formal methods to synt...
research
∙
03/07/2023