2022/06/15 by Başak Sakçak, Sakcak, Basak, Luca Bascetta +1
Engineering · Social Sciences · #Autonomous Vehicle Technology and Safety #Evacuation and Crowd Dynamics #FOS: Computer and information sciences #Robotics (cs.RO) #Urban Transport and Accessibility
paper · pdf · doi:10.48550/arxiv.2206.07498
openalex publication_date 2022/06/15 · openalex created_date 2022/06/18 · openalex updated_date 2026/07/28
In this paper, a robot navigating an environment shared with humans is considered, and a cost function that can be exploited in RRTX, a randomized sampling-based replanning algorithm that guarantees asymptotic optimality, to allow for a safe motion is proposed. The cost function is a path length weighted by a danger index based on a prediction of human motion performed using either a linear stochastic model, assuming constant longitudinal velocity and varying lateral velocity, and a GMM/GMR-based model, computed on an experimental dataset of human trajectories. The proposed approach is validated using a dataset of human trajectories collected in a real world setting.