광역 도심 배송을 위한 Efficient Grid 기반 경로 계획 알고리즘 연구
Research of the Efficient Grid-based Path Planning for Large-Scale Delivery in the Urban Environment
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초록
This study focuses on the path planning algorithm for large-scale autonomous delivery using drones and robots in urban environments. When generating delivery routes in urban environments, it is essential that avoid obstacles such as buildings, parking lots, or any other obstacles that could cause property damage. A commonly used method for obstacle avoidance is the grid-based A* algorithm. However, in large-scale urban environments, it is not feasible to set the resolution of the grid too high. If the grid cells are not sufficiently small during path planning, inefficient paths might be generated when avoiding obstacles, and smaller obstacles might be overlooked. To solve these issues, this study proposes a method that initially creates a low-resolution wide-area grid and then progressively reduces the grid cell size in areas containing registered obstacles to maintain real-time efficiency in generating paths. To implement this, obstacles in the operational area must first be registered on the map. When obstacle information is updated, the cells containing obstacles are processed as a primary subdivision, and cells closer to the obstacles are processed as a secondary subdivision. This approach is validated in a simulation environment and compared with the previous research according to the computing time and the path distance.
Abstract
This study focuses on the path planning algorithm for large-scale autonomous delivery using drones and robots in urban environments. When generating delivery routes in urban environments, it is essential that avoid obstacles such as buildings, parking lots, or any other obstacles that could cause property damage. A commonly used method for obstacle avoidance is the grid-based A* algorithm. However, in large-scale urban environments, it is not feasible to set the resolution of the grid too high. If the grid cells are not sufficiently small during path planning, inefficient paths might be generated when avoiding obstacles, and smaller obstacles might be overlooked. To solve these issues, this study proposes a method that initially creates a low-resolution wide-area grid and then progressively reduces the grid cell size in areas containing registered obstacles to maintain real-time efficiency in generating paths. To implement this, obstacles in the operational area must first be registered on the map. When obstacle information is updated, the cells containing obstacles are processed as a primary subdivision, and cells closer to the obstacles are processed as a secondary subdivision. This approach is validated in a simulation environment and compared with the previous research according to the computing time and the path distance.
참고문헌 (5)
- Jiang, Z., "Grid-Map-Based Path Planning and Task Assignment for Multi-Type AGVs in a Distribution Warehouse", Mathematics, 11(13), pp.1~20 (2023)
- Jung, S., "Collision-free local planner for unknown subterranean navigation", ETRI Journal, 43(4), pp.580~593 (2021)
- Lee, H., "Research of the Delivery Autonomy and Vision-based Landing Algorithm for Last-Mile Service using a UAV", Journal of Society of Korea Industrial and Systems Engineering, 46(2), pp.160~167 (2023)
- Lee, H., "The Research of Flexible Grid Size A* Path Planning Algorithm for the Drone Delivery in an Urban Environment", 2023 Proceeding of KSAS, pp.157~158 (2023)
- Popović, M., "An informative path planning framework for UAV-based terrain monitoring", Autonomous Robot, 44(12), pp.889~911 (2020)
