1 citations · 2 across the 8 of their papers we have counts for
9 papers · 1 filter
E2DRL: End-to-End Differentiable Reinforcement Learning for 3D Obstacle Avoidance in Quadruped Robots
Cheng Fan, Bingyang Zhou, Gang Yang +7
Differentiable reinforcement learning shows strong promise for robot policy learning, but its application to legged locomotion has remained limited to blind walking or simulated 2D…
DiagGen: Agentic Generation of Deformable Assets with Sim-based Diagnostics for Robotic Simulation
Guanxiong Chen, Yiduo Qu, Qianjun Xia +12
While simulation-ready deformable assets are essential for in-silico robotic manipulation tasks, existing generation frameworks typically assess physical plausibility after generat…
Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Guanxiong Chen, Qianjun Xia, Jiawei Peng +24
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover…
RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation
Pengzhi Yang, Xinyu Wang, Pengyu Jing +7
Reinforcement learning for robot manipulation is often bottlenecked by reward design, especially in long-horizon tasks: sparse success rewards provide weak supervision, while hand-…
Task-agnostic Lifelong Robot Learning with Retrieval-based Weighted Local Adaptation
Pengzhi Yang, Xinyu Wang, Ruipeng Zhang +3
A fundamental objective in intelligent robotics is to move towards lifelong learning robot that can learn and adapt to unseen scenarios over time. However, continually learning new…
Potato: A Data-Oriented Programming 3D Simulator for Large-Scale Heterogeneous Swarm Robotics
Jinjie Li, Liang Han, Haoyang Yu +4
Large-scale simulation with realistic nonlinear dynamic models is crucial for algorithms development for swarm robotics. However, existing platforms are mainly developed based on O…
Monocular Camera and Single-Beam Sonar-Based Underwater Collision-Free Navigation with Domain Randomization
Pengzhi Yang, Haowen Liu, Monika Roznere +1
Underwater navigation presents several challenges, including unstructured unknown environments, lack of reliable localization systems (e.g., GPS), and poor visibility. Furthermore,…
Policy Learning for Active Target Tracking over Continuous SE(3) Trajectories
Pengzhi Yang, Shumon Koga, Arash Asgharivaskasi +1
This paper proposes a novel model-based policy gradient algorithm for tracking dynamic targets using a mobile robot, equipped with an onboard sensor with limited field of view. The…
Learning Continuous Control Policies for Information-Theoretic Active Perception
Pengzhi Yang, Yuhan Liu, Shumon Koga +2
This paper proposes a method for learning continuous control policies for active landmark localization and exploration using an information-theoretic cost. We consider a mobile rob…