Multi-Robot Task Allocation -- Complexity and Approximation
Haris Aziz, Hau Chan, Ágnes Cseh, Bo Li, Fahimeh Ramezani, Chenhao Wang
- Year
- 2021
- Access
- Open access
Abstract
Multi-robot task allocation is one of the most fundamental classes of problems in robotics and is crucial for various real-world robotic applications such as search, rescue and area exploration. We consider the Single-Task robots and Multi-Robot tasks Instantaneous Assignment (ST-MR-IA) setting where each task requires at least a certain number of robots and each robot can work on at most one task and incurs an operational cost for each task. Our aim is to consider a natural computational problem of allocating robots to complete the maximum number of tasks subject to budget constraints. We consider budget constraints of three different kinds: (1) total budget, (2) task budget, and (3) robot budget. We provide a detailed complexity analysis including results on approximations as well as polynomial-time algorithms for the general setting and important restricted settings.
Keywords
Related papers
Dynamic reconfiguration in multi-robot agent systems using embedded language models
Shokhikha Amalana Murdivien, Jongsu Park, Jumyung Um
Robotics and Computer-Integrated Manufacturing · 2026
Hierarchical decision-making for UAVs’ game via LLM enhanced multi-agent reinforcement learning
Xinyu Dong, Bo Li, Guangyu Zhang +2 more
Aerospace Science and Technology · 2026
Formation optimization and obstacle avoidance decision-making methods for cooperative coverage search of multi-UUVs in underwater wreck areas
Haomiao Yu, Zeyuan Zhang, Yantian Ma
Robotics and Autonomous Systems · 2026
Human-in-the-Loop Swarms: A Bionic Swarm Approach to Real-World Soil Mapping
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu +3 more
2026