TY  - JOUR
PY  - 2023//
TI  - STP4: spatio temporal path planning based on pedestrian trajectory prediction in dense crowds
JO  - PeerJ Computer science
A1  - Sato, Yuta
A1  - Sasaki, Yoko
A1  - Takemura, Hiroshi
SP  - e1641
EP  - e1641
VL  - 9
IS  - 
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 2376-5992
UR  - http://dx.doi.org/10.7717/peerj-cs.1641
ID  - ref1
ER  -