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cs.RO2026

Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning

Shilin Shan, Chuhao Zhou, Ruize Wang +30

Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…

cs.RO2026

DreamTrajectory: Trajectory-Guided Action Generation with World Model Alignment for Mobile Manipulation

Zheng Yang, Wenjie Zhang, Xiangyu Chen +9

Mobile manipulation requires a robot to coordinate base and arm motion under continuously changing viewpoints and contact conditions, within an action space far larger than that of…

cs.RO2026

FORGE: Towards Functional Tool-Use Generalization via Keypoint Trajectory Reasoning

Chuhao Zhou, Liquan Wang, Shuxin Cao +5

While humans readily repurpose a book, a stone, or a shoe to drive a nail, robots trained on specific tools fail to transfer the same function to novel ones -- a gap we formalize a…

cs.RO2026

Rethinking Implicit Spatial Representation in Visuomotor Policy Learning

Xiangyu Chen, Yuxuan Hu, Chuhao Zhou +1

Generative model-based imitation learning has become a widely adopted paradigm for robotic manipulation, where policy performance depends critically on the conditioned visual repre…

cs.RO2026

Action-to-Action Flow Matching

Jindou Jia, Gen Li, Xiangyu Chen +5

Diffusion-based policies have recently achieved remarkable success in robotics by formulating action prediction as a conditional denoising process. However, the standard practice o…

cs.RO2026

Beyond Viewpoint Generalization: What Multi-View Demonstrations Offer and How to Synthesize Them for Robot Manipulation?

Boyang Cai, Qiwei Liang, Jiawei Li +11

Does multi-view demonstration truly improve robot manipulation, or merely enhance cross-view robustness? We present a systematic study quantifying the performance gains, scaling be…