354 citations · 843 across the 69 of their papers we have counts for
63 papers · 1 filter
Prim-LAfD: A Framework to Learn and Adapt Primitive-Based Skills from Demonstrations for Insertion Tasks
Zheng Wu, Wenzhao Lian, Changhao Wang +3
Learning generalizable insertion skills in a data-efficient manner has long been a challenge in the robot learning community. While the current state-of-the-art methods with reinfo…
Allowing Safe Contact in Robotic Goal-Reaching: Planning and Tracking in Operational and Null Spaces
Xinghao Zhu, Wenzhao Lian, Bodi Yuan +2
In recent years, impressive results have been achieved in robotic manipulation. While many efforts focus on generating collision-free reference signals, few allow safe contact betw…
Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning
Zheng Wu, Yichen Xie, Wenzhao Lian +5
Humans are capable of abstracting various tasks as different combinations of multiple attributes. This perspective of compositionality is vital for human rapid learning and adaptio…
Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learning
Jinning Li, Chen Tang, Masayoshi Tomizuka +1
Offline Reinforcement learning (RL) has shown potent in many safe-critical tasks in robotics where exploration is risky and expensive. However, it still struggles to acquire skills…
Autonomous Vehicle Parking in Dynamic Environments: An Integrated System with Prediction and Motion Planning
Jessica Leu, Yebin Wang, Masayoshi Tomizuka +1
This paper presents an integrated motion planning system for autonomous vehicle (AV) parking in the presence of other moving vehicles. The proposed system includes 1) a hybrid envi…
Long-Horizon Motion Planning via Sampling and Segmented Trajectory Optimization
Jessica Leu, Michael Wang, Masayoshi Tomizuka
This paper presents a hybrid robot motion planner that generates long-horizon motion plans for robot navigation in environments with obstacles. We propose a hybrid planner, RRT* wi…