Performance analysis of a random search algorithm for distributed autonomous mobile robots

This thesis presents a cooperative random search algorithm for distributed autonomous mobile robots. In particular, we are developing an algorithm that enables a team of homogeneous robots, without localisation capabilities and using limited communications, to search for targets in an unknown bounded structured environment. Our search algorithm consists of five simple behavioural rules for each robot and is implemented on physical robots. Following this, we performed multiple simulation experiments to analyse the system performance. The time taken to find all targets is used to measure performance. The results obtained demonstrated that the rule set is effective and robust to changes in the robotsa?? starting positions and targetsa?? locations. We found that system performance improves with increasing number of robots. It also depends on the size of the robots. Lastly, we formulated a benefit function that takes into account cost considerations to evaluate the benefit of increasing the number of robots.

Author dc:creator

• CHENG CHEE KONG

• cooperative robotics, distributed robotics, multi-robot systems, search, behaviour-based robotics, swarm intelligence