Heat mapping for improved victim detection

Disasters, such as earthquakes or tsunamis, result in destroyed buildings and other dangerous scenarios for human rescuers. Remotely controlled robots are often used to aid humans. Since those robots require steady communication, they are limited to a certain range and might get stuck in case the connection is interrupted. To augment remote controlled robots, autonomous robots are needed. These robots are able to navigate in devastated areas to detect victims while creating a map of the environment at the same time. Victim detection based on thermal sensors is the most widely used approach. In this paper we present a novel approach based on low-cost thermal sensors, using the global heat distribution. Therefore we developed a 2D heat map, which is created by the combination of thermal and laser information during continuous autonomous exploration. The map is build from the history of all sensor readings over time resulting in a heat distribution. The main contribution of this paper is the introduction of a 2D heat map accumulating thermal sensor readings over time for improved victim detection.