Citation

Sato Y, Sasaki Y, Takemura H. PeerJ Comput. Sci. 2023; 9: e1641.

Copyright

(Copyright © 2023, PeerJ)

DOI

10.7717/peerj-cs.1641

PMID

38077592

PMCID

PMC10703004

Abstract

This article proposes a means of autonomous mobile robot navigation in dense crowds based on predicting pedestrians' future trajectories. The method includes a pedestrian trajectory prediction for a running mobile robot and spatiotemporal path planning for when the path crosses with pedestrians. The predicted trajectories are converted into a time series of cost maps, and the robot achieves smooth navigation without dodging to the right or left in crowds; the path planner does not require a long-term prediction. The results of an evaluation implementing this method in a real robot in a science museum show that the trajectory prediction works. Moreover, the proposed planning's arrival times is 26.4% faster than conventional 2D path planning's arrival time in a simulation of navigation in a crowd of 50 people.

Language: en

Keywords

Dynamic environment; Mobile robot; Path planning; Pedestrian trajectory prediction