6 papers
Robo-ValueRL: Reliable Value Estimation for Offline-to-Online Reinforcement Learning
Wenke Xia, Pei Ren, Wenbo Yu +10
Offline-to-online reinforcement learning is promising for generalizable robotic manipulation, yet its full-stack complexity obscures reproduction and diagnosis. Within such systems…
GeCo-SRT: Geometry-aware Continual Adaptation for Robotic Cross-Task Sim-to-Real Transfer
Wenbo Yu, Wenke Xia, Weitao Zhang +1
Bridging the sim-to-real gap is important for applying low-cost simulation data to real-world robotic systems. However, previous methods are severely limited by treating each trans…
When would Vision-Proprioception Policies Fail in Robotic Manipulation?
Jingxian Lu, Wenke Xia, Yuxuan Wu +2
Proprioceptive information is critical for precise servo control by providing real-time robotic states. Its collaboration with vision is highly expected to enhance performances of…
Human-assisted Robotic Policy Refinement via Action Preference Optimization
Wenke Xia, Yichu Yang, Hongtao Wu +3
Establishing a reliable and iteratively refined robotic system is essential for deploying real-world applications. While Vision-Language-Action (VLA) models are widely recognized a…
Phoenix: A Motion-based Self-Reflection Framework for Fine-grained Robotic Action Correction
Wenke Xia, Ruoxuan Feng, Dong Wang +1
Building a generalizable self-correction system is crucial for robots to recover from failures. Despite advancements in Multimodal Large Language Models (MLLMs) that empower robots…
AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensors
Ruoxuan Feng, Jiangyu Hu, Wenke Xia +5
Visuo-tactile sensors aim to emulate human tactile perception, enabling robots to precisely understand and manipulate objects. Over time, numerous meticulously designed visuo-tacti…