This study presents a decentralised navigation algorithm for a team of mobile robots to traverse an unknown obstacle-ridden environment to detect and trap a target located in the region.
The proposed navigational strategy guarantees that the robots maintain the minimum distance allowed to the obstacles while avoiding them to trap the target.
The area was occupied by many obstacles with multiple shapes that were randomly distributed in the region; therefore, each robot had to find the safest path between the obstacles based on a decision-making algorithm when there was more than one path to choose from.
Unlike the conventional method of collecting information by mobile robots based on sampling in short and pre-set periods, in the proposed method robots collected information at indeterminate intervals leading to reductions in the sensing period, computation and consequent energy consumption.
The mathematical proof and the computer simulation confirmed the reliability and robustness of the proposed method.