Priority exploration by mobile robots for search and rescue situations
Arturo G. Roa-Borbolla, Antonio Marı́n-Hernández, Ericka Janet Rechy-Ramirez, Héctor Vázquez-Leal · 2017
Under disaster situations the time to rescue victims is as important as the lives of rescue teams. Autonomous mobile robots can be used to explore the dangerous areas in order to avoid exposing humans to these hazard situations. However, robots need to be intelligently programmed to explore efficiently the environment. Moreover, robots need to consider several conditions and knowledge of the environment to provide priority to more crowded spaces and ignore the unoccupied ones. This study introduces a priority path planning for search and rescue situations using mobile robots. A weighted (priority) graph representing a-priori information about the population of each space in a public building is used for intelligent path planning. Therefore, the resulting path is the shortest path with a maximum gain, i.e. fastest exploration and/or more information gain (victims detected), information that should be send to the rescue teams in order to proceed efficiently.