Performance-aware exploration algorithm for search and rescue robots

Autonomous exploration planning for multi-robot inside unknown, confined and cluttered environments is one of the main challenges for search and rescue robots. Evaluation and comparison of exploration algorithms inside various simulated search fields is crucial to attain fast victim localisation. Thus in this paper we discuss an algorithmic development and proliferation of realistic after-disaster test fields. Furthermore we evaluate a performance-aware exploration algorithm inside various developed search fields. We ascertain that it is possible to reduce the overall victim discovery time significantly, relative to an unstructured search algorithm across environments of a range of complexities. Moreover, it is possible to achieve performance that approaches to our optimal victim discovery time.