On the enhancement of firefighting robots using path-planning algorithms

Fire-fighting robots provide valuable support in fire-fighting operations. However, while operating in large indoor environments, most of the fire-fighting robots have to patrol the area to ensure that they detect the fire. This may result in the delay of fire detection and waste battery power. The paper discusses the implementation of a path-planning algorithm to achieve the most efficient path autonomously. This would enable the robot to reach the required target position in the fastest time possible. Four path-planning algorithms, namely Probabilistic Roadmaps, Rapidly Exploring Random Tree, Rapidly Exploring Random Tree Star, and A star (A*) were investigated. The performances of the algorithms were compared based on the computational time taken to generate the path and path length. From the simulation results obtained, it was determined that A* algorithm was an effective algorithm and was hence chosen for path-planning.