Proactively Approaching Pedestrians with an Autonomous Mobile Robot in Urban Environments

This paper presents a trajectory planning method enabling autonomous robots to approach people in dynamic environments to initiate a conversation proactively. It is shown how integrating human inspired parameters in optimal control based motion planning enables people to predict and read the purpose of a motion more easily.

Experimental evaluations in literature propose to incorporate human-like aspects since the intended action becomes more comprehensible for humans. Therefore, factors like approach speed, distance to the person, positioning near the person, trajectory shape, and the avoidance method are adopted from human behavior to generate motions. The presented trajectory planner is designed to improve the human-like appearance of an approach motion implementing these aspects. Human-likeness is evaluated according to naturalness and comfort of the approach behavior. By executing corresponding trajectories, the approach movement appears more natural and the intended action is easier to predict for humans.

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.