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REDIRECT: A 1% Fix for Bad Robot Habits
Yu Zhang, Jiazhuo Li, Yancong Wei +3
Robots can acquire bad habits from a few defective moments in otherwise useful teleoperation. In mixed-quality robot data, normal and problematic demonstrations share most task beh…
DeViGrasp: Robust Visual Mobile Grasping for Quadruped Manipulators under Degraded Perception
Liang Zhou, Jiaming Su, Yancong Wei +2
Quadruped manipulators enable mobile grasping in complex environments, yet their whole-body control policies remain vulnerable to unreliable onboard visual perception. Existing met…
Rethinking Demonstration Unlearning in Imitation Learning for Robotics
Jiazhuo Li, Yu Zhang, Yiming Fei +4
Imitation learning for robotics depends on human demonstrations, some of which people may later ask to remove. Retraining without them is the natural reference, but its cost grows…
SoftVTBench: A Deformation-Aware Visuo-Tactile Dataset and Benchmark for Deformable-Object Manipulation
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Physical interaction quality is central to deformable-object manipulation, yet most benchmarks evaluate task success alone. A policy may complete the task while allowing slip or ca…
SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects (Early Version)
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Deformable object manipulation poses challenges beyond task completion: successful execution must also maintain safe physical interaction, holding the object stably without slip or…
Push-Wiper: Toward General-Purpose Robotic Cleaning across Varied Stains and Surfaces with Segmented Pushing Trajectories
Renhao Lu, Mingxin Wang, Chenyang Cao +5
Viscous stains, characterized by high viscosity and complex rheological properties, remain a major challenge for robotic surface cleaning. Conventional wiping often spreads the sta…
ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts
Mingxin Wang, Bin Hu, Bin Qian +12
World Action Models (WAMs) have emerged as a promising paradigm by jointly modeling robot actions and future visual dynamics. However, their reliance on pixel-generative future sup…
Stage-Transition Dense Reward Modeling for Reinforcement Learning
Yang Yang, Bingjie Chen, Zihan Wang +4
Reinforcement learning for long-horizon robotic manipulation is often limited by sparse and delayed rewards, while manually designing dense shaping signals is costly and brittle to…
OVAL: Open-Vocabulary Augmented Memory Model for Lifelong Object Goal Navigation
Jiahua Pei, Yi Liu, Guoping Pan +3
Object Goal Navigation (ObjectNav) refers to an agent navigating to an object in an unseen environment, which is an ability often required in the accomplishment of complex tasks. W…
GGD-SLAM: Monocular 3DGS SLAM Powered by Generalizable Motion Model for Dynamic Environments
Yi Liu, Haoxuan Xu, Hongbo Duan +5
Visual SLAM algorithms achieve significant improvements through the exploration of 3D Gaussian Splatting (3DGS) representations, particularly in generating high-fidelity dense maps…
PRIOR: Perceptive Learning for Humanoid Locomotion with Reference Gait Priors
Chenxi Han, Shilu He, Yi Cheng +2
Training perceptive humanoid locomotion policies that traverse complex terrains with natural gaits remains an open challenge, typically demanding multi-stage training pipelines, ad…
PhaForce: Phase-Scheduled Visual-Force Policy Learning with Slow Planning and Fast Correction for Contact-Rich Manipulation
Mingxin Wang, Zhirun Yue, Renhao Lu +7
Contact-rich manipulation requires not only vision-dominant task semantics but also closed-loop reactions to force/torque (F/T) transients. Yet, generative visuomotor policies are…
PMG: Parameterized Motion Generator for Human-like Locomotion Control
Chenxi Han, Yuheng Min, Zihao Huang +4
Recent advances in data-driven reinforcement learning and motion tracking have substantially improved humanoid locomotion, yet critical practical challenges remain. In particular,…