On-line adaptive side-by-side human robot companion in dynamic urban environments

Abstract

This paper presents an adaptive side-by-side human-robot companion approach for navigation in urban dynamic environments, based on the anticipative kinodynamic planning. The adaptive means that the robot is capable of adjusting its motion to the behavior of the person being accompanied. Our main objective is to optimize in real time the path performed by the pair human-robot, by modifying dynamically the angle and distance between both throughout different locations of the path. We have defined a new cost function for finding the best planned path that takes into account the cost of the geometrical configuration between the human and the robot. Moreover, we have modified the Extended Social Force Model (SFM) to include the required forces to maintain the angle and distance between the robot and human while the human-robot pair is moving towards the shared goal. The method has been validated throughout a large set of simulations and real-live experiments.