Continual planning for search and rescue robots

The deployment of robots for emergency response tasks such as search and rescue is a promising application of robotics with growing importance. Given the perilous nature of these tasks, autonomous robot operation is highly desirable in order to reduce the risk imposed on the human rescue team. While much work has been done on creating robotic systems that can be deployed for search and rescue, limited work has been devoted to devise efficient real-time automated planning algorithms for these tasks. In this work, we present REDHI, an efficient algorithm for solving probabilistic models of complex problems such as search and rescue. We evaluate our algorithm on the search and rescue problem using both an abstract domain representation and a semi-realistic simulator of an existing robot system. The results show that REDHI can obtain near optimal performance with negligible planning time.