Path Planning Method for Securing Social Space in Narrow Passages
Taehoon Kim, Joono Cheong · 2024
In autonomous mobile robot applications, there are situations where the robot and people need to pass through a narrow space that is less than $1 \sim 2$ meter wide. Dijkstra or other global path planning algorithms tend to follow the center of narrow passageways to avoid collision. This may block the path of people who need to pass through the space. To resolve this issue, we propose an algorithm that yields biased path planning for autonomous robot in narrow spaces. The proposed algorithm tries to generate a left or right biased navigation path by marching with expandable bubbles to secure sufficient distance for a person to pass through even in narrow spaces. Real-world experiments are presented to validate the effectiveness of thee biased path planning algorithm in enabling safe human-robot coexistence in narrow and complex environments.