1 citations · 2 across the 8 of their papers we have counts for
4 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-…