A qualitative path planner for robot navigation using human-provided maps

Abstract

A method for controlling a mobile robot using qualitative inputs in the context of an approximate map, such as one sketched by a human, is presented. By defining a desired trajectory with respect to observable landmarks, human operators can send semi-autonomous robots into areas for which a true map is not available. Waypoint planning is formulated as a quadratic optimization problem which takes advantage of the probabilistic representation of the observed environment and the uncertain human input, resulting in robot trajectories in the true environment that are qualitatively similar to those provided by the human. This paper formally presents a methodology in which waypoints are extracted from a hand-drawn sketch, and obstacle avoidance is naturally accommodated through the addition of constraints in the optimization problem. A sensitivity analysis is performed to study how map distortions, sensor constraints, and a priori knowledge of the map orientation affect the performance of the planner. Lastly, a set of user studies is presented to demonstrate the robustness of the planner to different users’ sketched maps and to illustrate the efficacy of such a method for mobile robot control.