Self-Optimizing Human-Robot Systems for Search and Rescue in Disaster Scenarios

The increasing capabilities of robot systems enable new fields of practical applications for individual robots as well as multi-robot systems. But for some application scenarios like a fire or earthquake disaster current robots are still too limited to act fully autonomously in the disaster area. To overcome these limitations we consider a heterogeneous team of humans and robots complementing each other. Core application considered in this paper is a large burning warehouse with smoke making it difficult for fire fighters to search the building and to orientate themselves inside the warehouse. Therefore, an assisting team of robots is surrounding the fire fighters searching the proximity, providing orientation data, and establishing a wireless communication infrastructure on a basis of a mobile ad-hoc network. The adaptation of the robots is achieved by applying principles of selfoptimization on different levels of the human-robot system.