Planning stable paths for urban search and rescue robots

Rescue robots are platforms designed to operate in challenging and uneven surfaces. These robots are often equipped with manipulator arms and varying traction arrangements. As such, it is possible to reconfigure the kinematic of robot in order to reduce potential instabilities, such as those leading to vehicle tip-over. This paper proposes a methodology to plan feasible paths through uneven topographies by planning stable paths that account for the safe interaction between vehicle and terrain. The proposed technique, based on a gradient stability criterion, is validated with two of the best known path search strategies in 3D lattices, i.e. the A* and the Rapidly-Exploring Random Trees. Using real terrain data, simulation results obtained with the model of a real rescue robot demonstrate significant improvements in terms of paths that are able to automatically avoid regions of potential instabilities, to concentrate on those where the freedom of exploiting posture adaptation permits generation of optimally safe paths.