Abstract
Auction-based and threshold-based are the prevalent approaches for multi-robot distributed task allocation problem. We study the performance of these two approaches under a multi-objective dynamic task allocation scenario. The fuzzy inference system (FIS) is used in the auction-based approach to convert the objectives into a representative bid value. Experiments reveal that FIS auction-based outperforms the adaptive threshold-based approach in terms of load balancing. In contrast, the adaptive threshold-based approach produces better results in terms of traveled distance. Moreover, both approaches can achieve the same quality satisfaction objective.
| Original language | English |
|---|---|
| Article number | 87 |
| Journal | SN Computer Science |
| Volume | 2 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2021 |
Bibliographical note
Publisher Copyright:© 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature.
Keywords
- Auction-based task allocation
- Fuzzy inference system
- Multi-robot system
- Multi-robot task allocation (MRTA)
- Task quality
- Threshold-based task allocation
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Networks and Communications
- Computer Science Applications
- General Computer Science
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design