[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83780-en":3,"doc-seo-83780-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},83780,4398048950312,"Violet","https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908",8,"Research & Report","Conflict-Based Lazy Search for Fast Multi-Manipulator Planning","Employing multiple manipulators can raise task efficiency, yet real-time planning in cluttered workspaces remains difficult for multi-robot motion-planning algorithms. This paper introduces Conflict-Based Lazy Search (CBLS) for multi-manipulator planning, extending Conflict-Based Search (CBS). CBLS accelerates planning by precomputing a sparsified single-manipulator graph and using Lazy Edgedbased A* (LEA*) to reduce costly edge evaluations via lazy search and an edge queue. The method improves SAPF edge efficiency versus A* and is validated in comparisons with CBS and RRT-Connect.","Conflict-Based Lazy Search for Fast Multi-Manipulator Planning  \nDongliang Zheng, Member, IEEE, Zhipeng Wang, Member, IEEE, Siqi Wang, Yuxi Lu, Member, IEEE, Bin He, Senior Member, IEEE, Hesheng Wang, Senior Member, IEEE, and Panagiotis Tsiotras, Fellow, IEEE  \narXiv :2607 .04 124v 1 [ cs .RO] 5 Jul 2026  \nAbstract—Employing multiple manipulators can boost efficiency and accomplish tasks that a single manipulator cannot do. However, real-time planning for multiple manipulators in a cluttered workspace still poses significant challenges for planning algorithms. This paper proposes a new planning algorithm called Conflict-Based Lazy Search (CBLS) for multi-manipulator planning. CBLS is built on Conflict-Based Search (CBS), an efficient multi-agent pathfinding (MAPF) algorithm that has shown an order of magnitude speedup over previous approaches [1], [2]. CBS addresses MAPF by solving many single-agent pathfinding (SAPF) problems. Thus, its planning time directly depends on the efficiency of the SAPF algorithm adopted. Our CBLS algorithm enhances CBS with precomputation and lazy search. First, a lazily evaluated graph with controlled sparsity is precomputed for a single manipulator. Second, we propose the Lazy Edgedbased A* (LEA*) for efficient SAPF. Since edge evaluation is the computational bottleneck of manipulator planning, LEA* uses lazy search and an edge queue to reduce the number of edge evaluations. We show that LEA* is optimally vertex efficient and has improved edge efficiency compared to A*. We apply the proposed CBLS to multi-manipulator planning problems and show its superior performance by comparing it with CBS and a sampling-based algorithm, namely, RRT-Connect.  \nIndex Terms—Path planning, Conflict-based search, Lazy search, Manipulator planning, Multi-manipulator.  \nI. INTRODUCTION  \nFINDING optimal collision-free paths for multi-agent  \nsystems is an NP-hard problem, especially for multimanipulator systems operating in cluttered environments. Sampling-based motion planning methods such as PRM [3], RRT* [4], RRT\\# [5], and BIT* [6] make the problem tractable by approximating the search space using graphs or trees. They can also be viewed as graph-based methods. Graph search is used in PRM to find resolution-optimal paths, and local graph exploitation is used in RRT* to find asymptotically optimal paths. PRM builds a roadmap by drawing samples to cover  \nThis work was supported in part by the Science and Technology Commission of Shanghai Municipality (STCSM) under Grant 25ZR1404010, in part by the Shanghai Pujiang Program under Grant 25PJA140, in part by the National Natural Science Foundation of China under Grant 62088101, in part by the STCSM under Grant 2021SHZDZX0100, in part by the Fundamental Research Funds for the Central Universities.  \nDongliang Zheng, Zhipeng Wang, Siqi Wang, Yuxi Lu, and Bin He are with the Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai Institute of Intelligent Science and Technology, the State Key Laboratory of Autonomous Intelligent Unmanned Systems, and Frontiers Science Center for Intelligent Autonomous Systems of Ministry of Education, Tongji University, Shanghai 201203, China Email: [dzheng46@tongji.edu.cn](dzheng46@tongji.edu.cn) ; [wangzhipeng@tongji.edu.cn](wangzhipeng@tongji.edu.cn) ; [yuxilu@tongji.edu.cn](yuxilu@tongji.edu.cn) ;  \n[2310881@tongji.edu.cn](2310881@tongji.edu.cn) ; [binhe@tongji.edu.cn](binhe@tongji.edu.cn)  \nHesheng Wang is with the Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China. Email: [wanghesheng@sjtu.edu.cn](wanghesheng@sjtu.edu.cn)  \nPanagiotis Tsiotras is with the School of Aerospace Engineering and Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA. Email: [tsiotras@gatech.edu](tsiotras@gatech.edu)  \nFig. 1: Manipulator planning setup. Given a valid start-goal configuration pair of the manipulators, the CBLS algorithm generates a collision-f","cbCailjBLyDmtUok","https://ap.wps.com/l/cbCailjBLyDmtUok","pdf",12747431,4,1,11,"English","en",105,"# Abstract\n# Introduction\n## Multi-agent and multi-manipulator planning challenges\n## Sampling-based methods and MAPF background\n## Conflict-Based Search (CBS) and graph construction","[{\"question\":\"What problem does CBLS address in multi-manipulator planning?\",\"answer\":\"CBLS targets real-time planning of collision-free coordinated motions for multiple manipulators in cluttered environments, where planning is computationally challenging.\"},{\"question\":\"How does CBLS build on Conflict-Based Search (CBS)?\",\"answer\":\"CBLS is an extension of CBS, using CBS’s two-level scheme while improving the efficiency of the underlying single-agent planning (SAPF) component.\"},{\"question\":\"What are the key ideas behind LEA* used in CBLS?\",\"answer\":\"LEA* reduces edge-evaluation cost using lazy search and an edge queue, and it is presented as optimally vertex efficient with improved edge efficiency compared to 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problem does CBLS address in multi-manipulator planning?","Question",{"text":75,"@type":76},"CBLS targets real-time planning of collision-free coordinated motions for multiple manipulators in cluttered environments, where planning is computationally challenging.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does CBLS build on Conflict-Based Search (CBS)?",{"text":80,"@type":76},"CBLS is an extension of CBS, using CBS’s two-level scheme while improving the efficiency of the underlying single-agent planning (SAPF) component.",{"name":82,"@type":73,"acceptedAnswer":83},"What are the key ideas behind LEA* used in CBLS?",{"text":84,"@type":76},"LEA* reduces edge-evaluation cost using lazy search and an edge queue, and it is presented as optimally vertex efficient with improved edge efficiency compared to 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