arXiv Machine Learning

Learning from Humans for Proactive Assistance in Human-Robot Collaborative Transport

Hugging Face Trending Papers

Sep 21

Learning from Humans for Proactive Assistance in Human-Robot Collaborative Transport

We focus on human-robot collaborative transport, a challenging task of broad relevance spanning logistics, manufacturing, and the home, in which a user and a robot work together to relocate a large or...

llms robotics

arXiv AI

Jun 17

Moving Out: Physically-grounded Human-AI Collaboration

arXiv:2507. 18623v4 Announce Type: replace-cross Abstract: The ability to adapt to physical actions and constraints in an environment is crucial for embodied agents (e.

By Xuhui Kang, Sung-Wook Lee, Haolin Liu, Yuyan Wang, Yen-Ling Kuo

agents robotics benchmarks

arXiv AI

Jun 30

Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning

arXiv:2606. 28813v1 Announce Type: cross Abstract: Human videos are a scalable source of supervision for robot manipulation, as they are abundant and naturally capture rich object interactions.

By Shuo Cheng, Chuye Zhang, Alfred Cueva, Caelan Garrett, Ajay Mandlekar, Danfei Xu

robotics

arXiv Machine Learning

Jun 16

DemoDiffusion: One-Shot Human Imitation using pre-trained Diffusion Policy

arXiv:2506. 20668v3 Announce Type: replace-cross Abstract: We propose DemoDiffusion, a simple method for enabling robots to perform manipulation tasks by imitating a single human demonstration, without requiring task-specific training or paired human-robot data.

By Sungjae Park, Homanga Bharadhwaj, Shubham Tulsiani

diffusion reinforcement-learning robotics

arXiv AI

Sep 23

Cognition to Control - Multi-Agent Learning for Human-Humanoid Collaborative Transport

arXiv:2603.03768v2 Announce Type: replace-cross Abstract: Full-stack human-robot collaboration (HRC) can become brittle when replacing a planner, partner model, coordination policy, or controller cha...

By Hao Zhang, Yisen Li, Ruize Geng, Yves Tseng, Yaru Niu, Ding Zhao, H. Eric Tseng

llms agents reinforcement-learning robotics multimodal

arXiv AI

Jun 17

DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation

arXiv:2605. 31286v2 Announce Type: replace-cross Abstract: Real-world household robots require Vision-Language-Action (VLA) foundation models that can acquire reusable manipulation skills across diverse objects, task conditions, and household environments.

By Taiyi Su, Jian Zhu, Tianjian Wang, Youzhang He, Zitai Huang, Jianjun Zhang, Chong Ma, Hanyang Wang, Tianjiao Zhang, Munan Yin, Weihao Ding, Yi Xu

llms diffusion robotics efficiency multimodal benchmarks safety

arXiv AI

Jun 11

CHORUS: Decentralized Multi-Embodiment Collaboration with One VLA Policy

arXiv:2606. 12352v1 Announce Type: cross Abstract: Multi-robot collaboration allows robots to efficiently take on a wide range of tasks, from moving a couch through a doorway to assembling structures on a construction site.

By Ria Doshi, Tian Gao, Annie Chen, Chelsea Finn, Jeannette Bohg

robotics multimodal safety

arXiv Machine Learning

Jul 31

REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning

arXiv:2603. 13707v3 Announce Type: replace-cross Abstract: Humanoid loco-manipulation requires coordinated task-space motion planning with stable loco-manipulation command tracking under complex robot-environment dynamics and long-horizon tasks.

By Zhaoyuan Gu, Yipu Chen, Zimeng Chai, Alfred Cueva, Thong Nguyen, Yifan Wu, Huishu Xue, Minji Kim, Isaac Legene, Fukang Liu, KyoungMok Kim, Ayan Barula, Yongxin Chen, Ye Zhao

diffusion reinforcement-learning robotics fine-tuning

arXiv Computer Vision

Sep 22

AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation

arXiv:2609.22332v1 Announce Type: cross Abstract: Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act...

By Jiadi You, Qize Yu, Yue Chen, Minghong Cai, Zhide Zhong, Yuran Wang, Bowen Ping, Jiaqi Liang, Zhenhao Shen, Haodong Yan, Yinchuan Li, Ruihai Wu, Xiaojuan Qi, Yingcong Chen

llms diffusion robotics multimodal

arXiv Machine Learning

Jul 16

HRIBench: Benchmarking Interaction-Centric Human-Robot Collaboration

arXiv:2607. 13056v1 Announce Type: cross Abstract: Current vision-language-action (VLA) benchmarks primarily evaluate isolated manipulation skills while leaving human-robot interaction structure largely unmodeled.

By Chang Liu, Jiawei Zhang, Tao Zhang, Ye Wang, Hongyu Zhou, Qin Jin

agents robotics fine-tuning multimodal benchmarks safety

arXiv AI

Jul 2

Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration

arXiv:2607. 00033v1 Announce Type: cross Abstract: Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains challenging.

By Xinghao Zhu, Zixi Liu, Shalin Jain, Chenran Li, Milad Noori, Huihua Zhao, John Welsh, Michael Andres Lin, Wei Liu, Tingwu Wang, Xingye Da, Zhengyi Luo, Vishal Kulkarni, Naema Bhatti, Yuke Zhu, Linxi Fan, Bowen Wen, Danfei Xu, Soha Pouya, Yan Chang

reinforcement-learning robotics benchmarks

arXiv AI

Jul 20

SLAC: Safe and Efficient Real-Robot Reinforcement Learning via Unsupervised Simulation Pre-Training

arXiv:2506. 04147v5 Announce Type: replace-cross Abstract: Building capable household and industrial robots requires mastering the control of versatile, high-degree-of-freedom (DoF) systems such as mobile manipulators.

By Jiaheng Hu, Peter Stone, Roberto Mart\'in-Mart\'in

reinforcement-learning robotics benchmarks safety

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