Semi-autonomous exploration with robot teams in urban search and rescue

Abstract

This paper presents the development of a semi-autonomous exploration approach for a rescue robot team exploring unknown urban search and rescue (USAR) environments. The approach consists of a direction-based exploration technique utilized by multiple robots to search an unknown cluttered environment. The technique uses an occupancy grid approach that uniquely considers: 1) the terrain information of an environment by classifying obstacle cells as climbable or non-climbable cells, as well as 2) the direction of approach of a robot into a cell in order to determine a robot's ability to traverse a cell of interest. A distance threshold technique is employed to determine when the robots in a team should share this information with each other to minimize exploration overlap. The performance of the direction-based semi-autonomous exploration approach was investigated and compared to autonomous exploration of the same robot teams in simulations conducted in USARSim. The results verified that there was a statistically significant increase in exploration coverage using the semi-autonomous exploration mode over the fully autonomous exploration mode. The simulations also verified the potential use of semi-autonomous exploration of a team with multiple rescue robots.