The pursuit of multi-agent exploration is driven by its capacity to enhance operational robustness and efficiency in complex, dynamic environments, paving the way for advancements in autonomous systems and robotics. This thesis explores the development and assessment of decentralised planning algorithms within multi-agent systems, using the CARLA simulation environment. A methodology combining simulation-based testing and theoretical analysis was employed to evaluate the efficiency, and scalability of various decentralised planning strategies. The study systematically analysed three different exploration strategies for multi-agent systems: Greedy, MinPos, and Hungarian Assignments, across various configurations concerning the number of agents and communication demands. The Hungarian Assignment strategy demonstrates the highest efficiency in area coverage and coordination, especially as the number of agents increases. Meanwhile, the Greedy Assignment strategy requires the least communication bandwidth, indicating its potential for scenarios with limited communication capabilities. The MinPos Assignment, while facilitating better spatial distribution of agents than the Greedy Assignment, showed a moderate increase in communication demands and did not significantly outperform the Greedy Assignment in terms of efficiency. This work contributes to the field by providing insights into the trade-offs between exploration efficiency and communication overhead in multi-agent systems. Future work could explore synchronisation mechanisms, collision-avoidance strategies, and further decentralisation of the system's components.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-205544 |
| Date | January 2024 |
| Creators | Andersson, Alfred |
| Publisher | Linköpings universitet, Institutionen för systemteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0018 seconds