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The task of the multi-agent pathfinding (MAPF) problem is to navigate a team of agents from their start point to the goal points. However, this setup is unsuitable in the assembly line scenario, which is periodic with a long working hour.…

Multiagent Systems · Computer Science 2025-05-15 Mingkai Tang , Lu Gan , Kaichen Zhang

Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective start locations to their respective goal locations while minimizing path costs. Most existing MAPF algorithms rely on a common assumption…

Artificial Intelligence · Computer Science 2026-03-27 Xuemian Wu , Shizhe Zhao , Zhongqiang Ren

Routing strategies for traffics and vehicles have been historically studied. However, in the absence of considering drivers' preferences, current route planning algorithms are developed under ideal situations where all drivers are expected…

Robotics · Computer Science 2021-05-04 Jizhe Zhou , Qiwei Chen , Qin Li

High-speed multi-agent autonomous racing demands robust spatiotemporal planning and precise control under strict computational limits. Current methods often oversimplify interactions or abandon strict kinematic constraints. We resolve this…

Robotics · Computer Science 2026-03-11 Mingyi Zhang , Cheng Hu , Yiqin Wang , Haotong Qin , Hongye Su , Lei Xie

In this paper, we study the shortest path problem (SPP) with multiple source-destination pairs (MSD), namely MSD-SPP, to minimize average travel time of all shortest paths. The inherent traffic capacity limits within a road network…

Artificial Intelligence · Computer Science 2024-09-04 Jiaming Yin , Weixiong Rao , Yu Xiao , Keshuang Tang

Decentralized safe control plays an important role in multi-agent systems given the scalability and robustness without reliance on a central authority. However, without an explicit global coordinator, the decentralized control methods are…

Systems and Control · Electrical Eng. & Systems 2025-03-14 Yanze Zhang , Yiwei Lyu , Siwon Jo , Yupeng Yang , Wenhao Luo

This paper presents a new online multi-agent trajectory planning algorithm that guarantees to generate safe, dynamically feasible trajectories in a cluttered environment. The proposed algorithm utilizes a linear safe corridor (LSC) to…

Robotics · Computer Science 2022-01-04 Jungwon Park , Dabin Kim , Gyeong Chan Kim , Dahyun Oh , H. Jin Kim

Finding feasible, collision-free paths for multiagent systems can be challenging, particularly in non-communicating scenarios where each agent's intent (e.g. goal) is unobservable to the others. In particular, finding time efficient paths…

Multiagent Systems · Computer Science 2016-09-29 Yu Fan Chen , Miao Liu , Michael Everett , Jonathan P. How

We present an approach to ensure safe and deadlock-free navigation for decentralized multi-robot systems operating in constrained environments, including doorways and intersections. Although many solutions have been proposed that ensure…

Robotics · Computer Science 2025-01-28 Rohan Chandra , Vrushabh Zinage , Efstathios Bakolas , Peter Stone , Joydeep Biswas

Multi-Agent Path Finding (MAPF) is the problem of moving multiple agents from starts to goals without collisions. Lifelong MAPF (LMAPF) extends MAPF by continuously assigning new goals to agents. We present our winning approach to the 2023…

Multiagent Systems · Computer Science 2026-03-02 He Jiang , Yulun Zhang , Rishi Veerapaneni , Jiaoyang Li

Multi Agent Path Finding (MAPF) is critical for coordinating multiple robots in shared environments, yet robust execution of generated plans remains challenging due to operational uncertainties. The Action Dependency Graph (ADG) framework…

Multiagent Systems · Computer Science 2024-12-03 Joachim Dunkel

Decentralized multi-agent navigation under uncertainty is a complex task that arises in numerous robotic applications. It requires collision avoidance strategies that account for both kinematic constraints, sensing and action execution…

Robotics · Computer Science 2025-08-01 Stepan Dergachev , Konstantin Yakovlev

Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics, requiring the computation of collision-free paths for multiple agents moving from their respective start to goal positions. Coordinating multiple agents in a shared…

Robotics · Computer Science 2024-12-25 Jinhao Liang , Jacob K. Christopher , Sven Koenig , Ferdinando Fioretto

Addressing complex cooperative tasks in safety-critical environments poses significant challenges for multi-agent systems, especially under conditions of partial observability. We focus on a dynamic network bridging task, where agents must…

Multiagent Systems · Computer Science 2025-04-04 Raffaele Galliera , Konstantinos Mitsopoulos , Niranjan Suri , Raffaele Romagnoli

The Mutliagent Path Finding (MAPF) problem consists of identifying the trajectories that a set of agents should follow inside a given network in order to reach their desired destinations as soon as possible, but without colliding with each…

Computational Complexity · Computer Science 2025-06-03 Foivos Fioravantes , Dušan Knop , Jan Matyáš Křišťan , Nikolaos Melissinos , Michal Opler , Tung Anh Vu

In this work, we study the problem where a group of mobile agents needs to reach a set of goal locations, but it does not matter which agent reaches a specific goal. Unlike most of the existing works on this topic that typically assume the…

Multiagent Systems · Computer Science 2024-12-31 Stepan Dergachev , Konstantin Yakovlev

We present a scalable and effective multi-agent safe motion planner that enables a group of agents to move to their desired locations while avoiding collisions with obstacles and other agents, with the presence of rich obstacles,…

Robotics · Computer Science 2020-12-17 Jingkai Chen , Jiaoyang Li , Chuchu Fan , Brian Williams

The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision-free paths for a number of agents, from a set of start locations to a set of goal positions in a known 2D environment. MAPF has been studied in theoretical computer…

Artificial Intelligence · Computer Science 2019-05-22 Gleb Belov , Liron Cohen , Maria Garcia de la Banda , Daniel Harabor , Sven Koenig , Xinrui Wei

We focus on decentralized navigation among multiple non-communicating rational agents at \emph{uncontrolled} intersections, i.e., street intersections without traffic signs or signals. Avoiding collisions in such domains relies on the…

Robotics · Computer Science 2020-11-10 Junha Roh , Christoforos Mavrogiannis , Rishabh Madan , Dieter Fox , Siddhartha S. Srinivasa

We present an algorithm which modifies a deterministic pushdown automaton (DPDA) such that (i) the marked language is preserved, (ii) lifelocks are removed, (iii) deadlocks are removed, (iv) all states and edges are accessible, and (v)…

Formal Languages and Automata Theory · Computer Science 2014-03-24 Sven Schneider , Uwe Nestmann