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Date
2023-12Type
- Journal Article
ETH Bibliography
yes
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Abstract
Autonomous pedestrian-aware navigation in shared human-robot environments is a challenging problem. Here we consider a common situation in which a large crowd of pedestrians moves together in a limited space. Traditional planners struggle to find collision-free paths in such situations since the free space is limited and always changing. To solve this problem, we proposed a flow map-based RRT* method (FM-RRT*) containing a velocity layer and a minimally-intrusive layer. The proposed method models the velocity of the pedestrian flow and the area where the robot is less invasive to pedestrians. Furthermore, we propose an adaptive bias sampling, which drives the robot considering relative velocity, or minimal intrusion, according to the pedestrian flow. The evaluation is conducted in the Crowdbot Challenge simulator. The results show that our method can find a feasible path considering collision risk while simultaneously avoiding intrusive human movement. Show more
Publication status
publishedExternal links
Journal / series
IEEE Transactions on Intelligent Transportation SystemsVolume
Pages / Article No.
Publisher
IEEESubject
Pedestrians; Robots; Collision avoidance; Navigation; Path planning; Heuristic algorithms; Mobile robots; Mobile robot; path planning; human awareness; human-robot interactionMore
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ETH Bibliography
yes
Altmetrics