Proactively Approaching Pedestrians with an Autonomous Mobile Robot in Urban Environments

This paper presents a trajectory planning method enabling autonomous robots to approach persons in dynamic environments to start a conversation proactively. It is shown how integrating human inspired parameters in optimal control based motion planning increases the readability of a motion. The presented trajectory planner is designed to improve the human-like appearance of an approach motion. Experimental evaluations shown in literature propose to incorporate human-like aspects since the intended action becomes more comprehensible for humans. Factors like approach speed, distance to the person, positioning near the person, trajectory shape and the avoidance method draw on human behavior to generate motions accordingly. Human-likeness is evaluated by means of naturalness and comfort of the approach behavior. By executing corresponding trajectories, the approach movement appears more natural and the readability of the action is enhanced. The Interactive Urban RObot (IURO) project, where an autonomous robot queries passers-by to fill its knowledge gaps, poses a setting where approaching humans effectively is an essential ability for successful task completion. This paper formulates the motion planning procedure as an optimal control problem. Human-like behavior is generated through specific constraints and cost. In order to achieve correct timing, appropriate trajectory shape and the desired behavior for collision avoidance in a dynamic environment, the optimization is split into three consecutive steps. An implementation of a planning algorithm for dynamic environments, capable of online replanning, is proposed. Experiments conducted with this system showed the appropriateness of speed and distance parameters. Further statistical results confirmed that the shape of a trajectory significantly affects the naturalness of an approach motion. 1Institute of Automatic Control Engineering (LSR), Technische Universität München, D-80290 Munich, Germany 2Institute for Advanced Study, Technische Universität München, D-85748 Garching, Germany e-mail: {dc,a.turnwald,dw,mb}@tum.de