| Autor: |
Yuta Sato, Yoko Sasaki, Hiroshi Takemura |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
PeerJ Computer Science, Vol 9, p e1641 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2376-5992 |
| DOI: |
10.7717/peerj-cs.1641 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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