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In this paper, we consider the problem of Multi-Robot Path Planning (MRPP) in continuous space. The difficulty of the problem arises from the extremely large search space caused by the combinatorial nature of the problem and the continuous…

Robotics · Computer Science 2025-02-12 Joonyeol Sim , Joonkyung Kim , Changjoo Nam

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixed total priority ordering of all agents a priori. We instead…

Artificial Intelligence · Computer Science 2018-12-18 Hang Ma , Daniel Harabor , Peter J. Stuckey , Jiaoyang Li , Sven Koenig

We consider a system consisting of multiple mobile robots in which the user can at any time issue relocation tasks ordering one of the robots to move from its current location to a given destination location. In this paper, we deal with the…

Robotics · Computer Science 2015-02-02 Michal Čáp , Jiří Vokřínek , Alexander Kleiner

This work presents a decentralized motion planning framework for addressing the task of multi-robot navigation using deep reinforcement learning. A custom simulator was developed in order to experimentally investigate the navigation problem…

This paper presents a novel multi-robot coverage path planning (CPP) algorithm - aka SCoPP - that provides a time-efficient solution, with workload balanced plans for each robot in a multi-robot system, based on their initial states. This…

Purpose of Review Planning collision-free paths for multiple robots is important for real-world multi-robot systems and has been studied as an optimization problem on graphs, called Multi-Agent Path Finding (MAPF). This review surveys…

Robotics · Computer Science 2022-06-24 Hang Ma

We describe a novel approach for computing collision-free \emph{global} trajectories for $p$ agents with specified initial and final configurations, based on an improved version of the alternating direction method of multipliers (ADMM).…

Artificial Intelligence · Computer Science 2013-11-19 Jose Bento , Nate Derbinsky , Javier Alonso-Mora , Jonathan Yedidia

Autonomous robots are widely utilized for mapping and exploration tasks due to their cost-effectiveness. Multi-robot systems offer scalability and efficiency, especially in terms of the number of robots deployed in more complex…

Robotics · Computer Science 2025-06-04 Apoorva Vashisth , Manav Kulshrestha , Damon Conover , Aniket Bera

We present a centralized algorithm for labeled, disk-shaped Multi-Robot Path Planning (MPP) in a continuous planar workspace with polygonal boundaries. Our method automatically transform the continuous problem into a discrete, graph-based…

Robotics · Computer Science 2022-07-20 Liang He , Zherong Pan , Kiril Solovey , Biao Jia , Dinesh Manocha

We study the navigation problem for a robot moving amidst static and dynamic obstacles and rely on a hierarchical approach to solve it. First, the reference trajectory is planned by the safe interval path planning algorithm that is capable…

Robotics · Computer Science 2019-06-18 Konstantin Yakovlev , Anton Andreychuk , Juliya Belinskaya , Dmitry Makarov

Traditional multi-robot motion planning (MMP) focuses on computing trajectories for multiple robots acting in an environment, such that the robots do not collide when the trajectories are taken simultaneously. In safety-critical…

Robotics · Computer Science 2023-03-15 Justin Kottinger , Shaull Almagor , Morteza Lahijanian

The goal of Multi-Agent Path Finding (MAPF) is to find a set of paths for a fleet of agents moving in a shared environment such that the agents reach their goals without colliding with each other. In practice, some of the robots executing…

Multiagent Systems · Computer Science 2025-09-15 David Zahrádka , Denisa Mužíková , David Woller , Miroslav Kulich , Jiří Švancara , Roman Barták

The paper considers the problem of planning a set of non-conflict trajectories for the coalition of intelligent agents (mobile robots). Two divergent approaches, e.g. centralized and decentralized, are surveyed and analyzed. Decentralized…

Artificial Intelligence · Computer Science 2017-07-21 Anton Andreychuk , Konstantin Yakovlev

The problem of mixed static and dynamic obstacle avoidance is essential for path planning in highly dynamic environment. However, the paths formed by grid edges can be longer than the true shortest paths in the terrain since their headings…

Artificial Intelligence · Computer Science 2021-03-01 Junxiao Xue , Xiangyan Kong , Bowei Dong , Mingliang Xu

Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where a team of robots is tasked with transporting a set of tasks, each from an initial location and each to a specified target location. Appearing in the context of…

Multiagent Systems · Computer Science 2021-10-29 Zhe Chen , Javier Alonso-Mora , Xiaoshan Bai , Daniel D. Harabor , Peter J. Stuckey

Designing autonomous aerial robot team systems remains a grand challenge in robotics. Existing works in this field can be categorized as centralized and decentralized. Centralized methods suffer from scale dilemmas, while decentralized ones…

Robotics · Computer Science 2022-10-20 Jialiang Hou , Xin Zhou , Zhongxue Gan , Fei Gao

Finding asymptotically-optimal paths in multi-robot motion planning problems could be achieved, in principle, using sampling-based planners in the composite configuration space of all of the robots in the space. The dimensionality of this…

Multiagent Systems · Computer Science 2017-07-05 Andrew Dobson , Kiril Solovey , Rahul Shome , Dan Halperin , Kostas E. Bekris

We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that…

Robotics · Computer Science 2018-07-24 Fahad Islam , Oren Salzman , Maxim Likhachev

The aim of coordinated planning is to avoid robot-to-robot collisions in a multi-robot system, and there are two standard solution approaches: centralized planning and decoupled planning. Our first contribution is a decoupled planning…

Robotics · Computer Science 2024-01-17 Jonas Wittmann , Franziska Ochsenfarth , Valentin Sonneville , Daniel Rixen

This paper investigates Multi-Agent Path Finding Among Movable Obstacles (M-PAMO), which seeks collision-free paths for multiple agents from their start to goal locations among static and movable obstacles. M-PAMO arises in logistics and…

Robotics · Computer Science 2025-10-01 Shaoli Hu , Shizhe Zhao , Zhongqiang Ren