This work focuses on the dual-arm object rearrangement problem abstracted from a realistic industrial scenario of Cartesian robots. The goal of this problem is to transfer all the objects from sources to targets with the minimum total completion time. To achieve the goal, the core idea is to develop an effective object-to-arm task assignment strategy for minimizing the cumulative task execution time and maximizing the dual-arm cooperation efficiency. One of the difficulties in the task assignment is the scalability problem. As the number of objects increases, the computation time of traditional offline-search-based methods grows strongly for computational complexity. Encouraged by the adaptability of reinforcement learning (RL) in long-sequence task decisions, we propose an online task assignment decision method based on RL, and the computation time of our method only increases linearly with the number of objects. Further, we design an attention-based network to model the dependencies between the input states during the whole task execution process to help find the most reasonable object-to-arm correspondence in each task assignment round. In the experimental part, we adapt some search-based methods to this specific setting and compare our method with them. Experimental result shows that our approach achieves outperformance over search-based methods in total execution time and computational efficiency, and also verifies the generalization of our method to different numbers of objects. In addition, we show the effectiveness of our method deployed on the real robot in the supplementary video.
Synchronized Dual-arm Rearrangement via Cooperative mTSP
National University of Defense Technology（国防科技大学）；Shenzhen University（深圳大学）；Xiangjiang Laboratory（湘江实验室）；Hunan University of Technology and Business（湖南工商大学）
Implicit Articulated Robot Morphology Modeling with Configuration Space Neural Signed Distance Functions
École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）；Chalmers University of Technology（查尔姆斯理工大学）；University College London（伦敦大学学院）；Rice University（莱斯大学）；Massachusetts Institute of Technology（麻省理工学院）
Dual-arm Cooperation for Tabletop Wiping with Temporal Object Removal
School of Automation Science and Electrical Engineering, Beihang University（北京航空航天大学自动化科学与电气工程学院）；Beijing Institute for General Artificial Intelligence (BIGAI)（北京通用人工智能研究院）；Delta Intelligence（Delta智能）；State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University（北京大学智能科学与技术学院通用人工智能国家重点实验室）
EmbodiSteer: Steering Embodiment-Agnostic Visuomotor Policies with Joint-Space Guidance for Zero-Shot Cross-Embodiment Deployment
Department of Automation, Tsinghua University（清华大学自动化系）；Beijing Key Laboratory of Embodied Intelligence Systems（北京具身智能系统重点实验室）；Institute for Embodied Intelligence and Robotics, Tsinghua University（清华大学具身智能与机器人研究所）
Graph-Fused Vision-Language-Action for Policy Reasoning in Multi-Arm Robotic Manipulation
Machine Learning and I-health International Cooperation Base of Zhejiang Province, Artificial Intelligence Institute, Hangzhou Dianzi University, Zhejiang（浙江省机器学习与健康国际合作基地、人工智能学院、杭州电子大学）；Electrical and Computer Engineering Department, The University of New Mexico（新墨西哥大学电气与计算机工程系）；School of Computation, Information and Technology, Technical University of Munich（慕尼黑技术大学计算、信息与技术学院）
Information-Theoretic Graph Fusion with Vision-Language-Action Model for Policy Reasoning and Dual Robotic Control
Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, United States, 87106（电气与计算机工程系，新墨西哥大学，阿尔伯克基，美国，87106）；Dynamic Robot Systems Group, Oxford Robotics Institute, University of Oxford, United Kingdom, OX26NN（动态机器人系统组，牛津机器人研究所，牛津大学，英国，OX26NN）；Mechanical and Aerospace Engineering Department, The George Washington University, DC, United States, 22202（机械与航空航天工程系，乔治华盛顿大学，华盛顿特区，美国，22202）；Department of Computer Science, University of Alabama at Birmingham, Alabama, United States, 35294（计算机科学系，阿拉巴马大学伯明翰分校，阿拉巴马，美国，35294）；The School of Computation, Information and Technology, Technical University of Munich, Germany, 85748（计算、信息与技术学院，慕尼黑技术大学，德国，85748）；Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy, 20156（机械工程系，米兰理工学院，米兰，意大利，20156）
