Papers Multi-Agent Path Finding
“Multi-Agent Path Finding” 태그가 달린 논문 140편 · 필터 해제
A Conflict-Aware Optimal Goal Assignment Algorithm for Multi-Robot Systems
The fundamental goal assignment problem for a multi-robot application aims to assign a unique goal to each robot while ensuring collision-free paths, minimizing the total movement cost. A plausible algorithmic solution t…
Multi-Agent Path FindingOptimal Task Assignment and Path Planning using Conflict-Based Search with Precedence and Temporal Constraints
The Multi-Agent Path Finding (MAPF) problem entails finding collision-free paths for a set of agents, guiding them from their start to goal locations. However, MAPF does not account for several practical task-related con…
Multi-Agent Path FindingReinforcement Learning (RL)Guidance Graph Optimization for Lifelong Multi-Agent Path Finding
We study how to use guidance to improve the throughput of lifelong Multi-Agent Path Finding (MAPF). Previous studies have demonstrated that, while incorporating guidance, such as highways, can accelerate MAPF algorithms,…
Multi-Agent Path FindingMulti-agent Path Finding for Cooperative Autonomous Driving
Anticipating possible future deployment of connected and automated vehicles (CAVs), cooperative autonomous driving at intersections has been studied by many works in control theory and intelligent transportation across d…
Autonomous DrivingMulti-Agent Path FindingSchedulingScalable Mechanism Design for Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) involves determining paths for multiple agents to travel simultaneously and collision-free through a shared area toward given goal locations. This problem is computationally complex, espec…
Multi-Agent Path FindingWhy Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet
With the explosive influence caused by the success of large language models (LLM) like ChatGPT and GPT-4, there has been an extensive amount of recent work showing that foundation models can be used to solve a large vari…
Language ModelingLanguage ModellingLarge Language ModelMulti-Agent Path FindingBidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution
The Multi-Agent Path Finding (MAPF) problem involves planning collision-free paths for multiple agents in a shared environment. The majority of MAPF solvers rely on the assumption that an agent can arrive at a specific l…
Multi-Agent Path FindingAdaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in large-scale multi-agent systems. State-of-the-art anytime MAPF is based on Large Neighborhood Search (LNS), where a fast in…
Multi-Agent Path FindingThompson SamplingImproved Anonymous Multi-Agent Path Finding Algorithm
We consider an Anonymous Multi-Agent Path-Finding (AMAPF) problem where the set of agents is confined to a graph, a set of goal vertices is given and each of these vertices has to be reached by some agent. The problem is…
Multi-Agent Path FindingOptimizing Crowd-Aware Multi-Agent Path Finding through Local Communication with Graph Neural Networks
Multi-Agent Path Finding (MAPF) in crowded environments presents a challenging problem in motion planning, aiming to find collision-free paths for all agents in the system. MAPF finds a wide range of applications in vari…
Decision MakingMotion PlanningMulti-Agent Path Findingreinforcement-learningTraffic Flow Optimisation for Lifelong Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics that asks us to compute collision-free paths for a team of agents, all moving across a shared map. Although many works appear on this topic, all curren…
Multi-Agent Path FindingSACHA: Soft Actor-Critic with Heuristic-Based Attention for Partially Observable Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is a crucial component for many large-scale robotic systems, where agents must plan their collision-free paths to their given goal positions. Recently, multi-agent reinforcement learning h…
Multi-Agent Path FindingMulti-agent Reinforcement LearningSelective Communication for Cooperative Perception in End-to-End Autonomous Driving
The reliability of current autonomous driving systems is often jeopardized in situations when the vehicle's field-of-view is limited by nearby occluding objects. To mitigate this problem, vehicle-to-vehicle communication…
Autonomous DrivingMulti-Agent Path FindingFine-Grained Complexity Analysis of Multi-Agent Path Finding on 2D Grids
Multi-Agent Path Finding (MAPF) is a fundamental motion coordination problem arising in multi-agent systems with a wide range of applications. The problem's intractability has led to extensive research on improving the s…
Multi-Agent Path FindingOn Computing Universal Plans for Partially Observable Multi-Agent Path Finding
Multi-agent routing problems have drawn significant attention nowadays due to their broad industrial applications in, e.g., warehouse robots, logistics automation, and traffic control. Conventionally, they are modelled a…
Multi-Agent Path FindingTracking Progress in Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is an important core problem for many new and emerging industrial applications. Many works appear on this topic each year, and a large number of substantial advancements and performance im…
Multi-Agent Path FindingMulti-Robot Coordination and Layout Design for Automated Warehousing
With the rapid progress in Multi-Agent Path Finding (MAPF), researchers have studied how MAPF algorithms can be deployed to coordinate hundreds of robots in large automated warehouses. While most works try to improve the…
DiversityLayout DesignMulti-Agent Path FindingDouble-Deck Multi-Agent Pickup and Delivery: Multi-Robot Rearrangement in Large-Scale Warehouses
We introduce a new problem formulation, Double-Deck Multi-Agent Pickup and Delivery (DD-MAPD), which models the multi-robot shelf rearrangement problem in automated warehouses. DD-MAPD extends both Multi-Agent Pickup and…
Multi-Agent Path FindingThe Study of Highway for Lifelong Multi-Agent Path Finding
In modern fulfillment warehouses, agents traverse the map to complete endless tasks that arrive on the fly, which is formulated as a lifelong Multi-Agent Path Finding (lifelong MAPF) problem. The goal of tackling this ch…
Multi-Agent Path FindingRobust Multi-Agent Pickup and Delivery with Delays
Multi-Agent Pickup and Delivery (MAPD) is the problem of computing collision-free paths for a group of agents such that they can safely reach delivery locations from pickup ones. These locations are provided at runtime, …
Multi-Agent Path Finding