6 papers
Efficient Multi-Modal Planning with Reward-Guided Preference Optimization for Autonomous Driving
Chenglin Chen, Lujia Wang, Xinhu Zheng +2
Safe and efficient trajectory planning is essential in autonomous driving. However, existing end-to-end approaches often fall short in both computational efficiency and safety guar…
Tac4Loco: Learning Spatiotemporal Plantar Pressure Representations for Humanoid Locomotion
Ziyun Liu, Sikai Guo, Zheng Li +6
Humanoid robots are expected to traverse complex terrains, where the plantar support may vary dramatically due to foot placement errors, ground properties, and transient dynamics.…
HiFi-UMI: Learning Deployable Manipulation Policies from High-Fidelity UMI Data Alone
Simple AI, :, Yuteng Wei +16
Learning deployable manipulation policies is bottlenecked by the scarcity of data that is both high-fidelity and scalable. Real-robot teleoperation is accurate but costly to scale;…
OmniDP: Beyond-FOV Large-Workspace Humanoid Manipulation with Omnidirectional 3D Perception
Pei Qu, Zheng Li, Yufei Jia +5
The deployment of humanoid robots for dexterous manipulation in unstructured environments remains challenging due to perceptual limitations that constrain the effective workspace.…
Real-to-Sim for Highly Cluttered Environments via Physics-Consistent Inter-Object Reasoning
Tianyi Xiang, Jiahang Cao, Sikai Guo +3
Reconstructing physically valid 3D scenes from single-view observations is a prerequisite for bridging the gap between visual perception and robotic control. However, in scenarios…
ManiVID-3D: Generalizable View-Invariant Reinforcement Learning for Robotic Manipulation via Disentangled 3D Representations
Zheng Li, Pei Qu, Yufei Jia +6
Deploying visual reinforcement learning (RL) policies in real-world manipulation is often hindered by camera viewpoint changes. A policy trained from a fixed front-facing camera ma…