We study a fundamental NP-hard motion coordination problem for multi-robot/multi-agent systems: We are given a graph $G$ and set of agents, where each agent has a given directed path in $G$. Each agent is initially located on the first vertex of its path. At each time step an agent can move to the next vertex on its path, provided that the vertex is not occupied by another agent. The goal is to find a sequence of such moves along the given paths so that each reaches its target, or to report that no such sequence exists. The problem models guidepath-based transport systems, which is a pertinent abstraction for traffic in a variety of contemporary applications, ranging from train networks or Automated Guided Vehicles (AGVs) in factories, through computer game animations, to qubit transport in quantum computing. It also arises as a sub-problem in the more general multi-robot motion-planning problem.
We provide a fine-grained tractability analysis of the problem by considering new assumptions and identifying minimal values of key parameters for which the problem remains NP-hard. Our analysis identifies a critical parameter called vertex multiplicity (VM), defined as the maximum number of paths passing through the same vertex. We show that a prevalent variant of the problem, which is equivalent to Sequential Resource Allocation (concerning deadlock prevention for concurrent processes), is NP-hard even when VM is 3. On the positive side, for VM $\le$ 2 we give an efficient algorithm that iteratively resolves cycles of blocking relations among agents. We also present a variant that is NP-hard when the VM is 2 even when $G$ is a 2D grid and each path lies in a single grid row or column. By studying highly distilled yet NP-hard variants, we deepen the understanding of what makes the problem intractable and thereby guide the search for efficient solutions under practical assumptions.
Federated Single-Agent Robotics: Multi-Robot Coordination Without Intra-Robot Multi-Agent Fragmentation
School of Software, Harbin Institute of Technology（哈尔滨工业大学软件学院）；School of Computer Science and Technology, Harbin Institute of Technology（哈尔滨工业大学计算机科学与技术学院）；School of Mathematical and Computer Sciences, Heriot-Watt University, Malaysia Campus（赫瑞-沃顿大学马来西亚校区数学与计算机科学学院）；School of Future Science and Engineering, Soochow University（苏州大学未来科学与工程学院）
K-ARC: Adaptive Robot Coordination for Multi-Robot Kinodynamic Planning
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Siebel School of Computing and Data Science（西贝尔计算与数据科学学院）；Texas A&M University（德克萨斯农工大学）；Instituto Tecnológico Autónomo de México (ITAM)（墨西哥自治技术学院）
Safe and Socially Aware Multi-Robot Coordination in Multi-Human Social Care Settings
School of Computing and Communications, The Open University（奥本大学计算与通讯学院）；School of Electronics and Computer Science, University of Southampton（南安普顿大学电子与计算机科学学院）；School of Computer Science, University of Nottingham（诺丁汉大学计算机科学学院）
On Randomized Searching for Multi-robot Coordination
Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague（捷克布拉格捷克技术大学信息学、机器人学与控制论研究所）；Czech Technical University in Prague（布拉格捷克技术大学）
Multi-Robot Coordination for Planning under Context Uncertainty
Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University（俄勒冈州立大学协作机器人与智能系统研究所）；Khoury College of Computer Sciences, Northeastern University（东北大学库里计算机科学学院）
Failure-Aware Multi-Robot Coordination for Resilient and Adaptive Target Tracking
Department of Electrical and Computer Engineering, Drexel University（德雷塞尔大学电气与计算机工程系）；Institute for Robotics and Intelligent Machines, Georgia Institute of Technology（佐治亚理工学院机器人与智能机器研究所）；GRASP Lab, University of Pennsylvania（宾夕法尼亚大学GRASP实验室）
DeReCo: Decoupling Representation and Coordination Learning for Object-Adaptive Decentralized Multi-Robot Cooperative Grasping and Lifting
Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology (NAIST)（信息科学系，科学技术研究生院，科学与技术国立研究所（NAIST））；Department of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology（认知机器人系，机械工程学院，代尔夫特理工大学）
Efficient Coordination and Synchronization of Multi-Robot Systems Under Recurring Linear Temporal Logic
Department of Information Engineering, University of Padova（帕多瓦大学信息工程系）；Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology（皇家理工学院电气工程与计算机科学学院决策与控制系统系）
ACHORD: Communication-Aware Multi-Robot Coordination with Intermittent Connectivity
Jet Propulsion Laboratory, California Institute of Technology（加州理工学院喷气推进实验室）；Instituto Tecnológico Vale（淡水河谷技术研究所）；University of Southern California（南加州大学）；Cornell University（康奈尔大学）；University of California, Riverside（加州大学河滨分校）；Polytechnique Montréal（蒙特利尔理工学院）；Institut de Robòtica i Informàtica Industrial, CSIC-UPC（西班牙高等科学研究委员会-加泰罗尼亚理工大学机器人与工业信息研究所）；California Institute of Technology（加州理工学院）
