3 citations · 6 across the 11 of their papers we have counts for
7 papers · 1 filter
Absolute Policy Optimization
Weiye Zhao, Feihan Li, Yifan Sun +3
In recent years, trust region on-policy reinforcement learning has achieved impressive results in addressing complex control tasks and gaming scenarios. However, contemporary state…
A Lightweight and Transferable Design for Robust LEGO Manipulation
Ruixuan Liu, Yifan Sun, Changliu Liu
Lego is a well-known platform for prototyping pixelized objects. However, robotic Lego prototyping (i.e., manipulating Lego bricks) is challenging due to the tight connections and…
Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization
Yifan Sun, Feihan Li, Weiye Zhao +3
Deep reinforcement learning (RL) excels in various control tasks, yet the absence of safety guarantees hampers its real-world applicability. In particular, explorations during lear…
State-wise Constrained Policy Optimization
Weiye Zhao, Rui Chen, Yifan Sun +2
Reinforcement Learning (RL) algorithms have shown tremendous success in simulation environments, but their application to real-world problems faces significant challenges, with saf…
Robotic LEGO Assembly and Disassembly from Human Demonstration
Ruixuan Liu, Yifan Sun, Changliu Liu
This paper studies automatic prototyping using LEGO. To satisfy individual needs and self-sustainability, this paper presents a framework that learns the assembly and disassembly s…
GUARD: A Safe Reinforcement Learning Benchmark
Weiye Zhao, Yifan Sun, Feihan Li +4
Due to the trial-and-error nature, it is typically challenging to apply RL algorithms to safety-critical real-world applications, such as autonomous driving, human-robot interactio…
Hybrid Task Constrained Planner for Robot Manipulator in Confined Environment
Yifan Sun, Weiye Zhao, Changliu Liu
Trajectory generation in confined environment is crucial for wide adoption of intelligent robot manipulators. In this paper, we propose a novel motion planning approach for redunda…