Base pose estimation using shared reachability maps for manipulation tasks

Manipulation tasks for robots with a robotic arm and a mobile base are one of the most error-prone operations in service robotics. Especially for low-cost robots with a small reachable workspace of the arms, the selection of base poses for reaching tasks is a challenging problem. In this paper, we focus on the estimation of base poses for robots such that they are able to reach a given end effector target pose using space-efficient discretizations of the robots workspace, so-called reachability maps. We further present a method to share these reachability maps among robots by storing them on a cloud-database, annotated with a semantic description. These are then integrated in a knowledge-based task execution system for service robots. Last, we conclude with the results of an experiment showing the cooperation of robots of different hardware making use of each other´s reachability maps.