Unidirectional-Road-Network-Based Global Path Planning for Cleaning Robots in Semi-Structured Environments

Practical global path planning is critical for commercializing cleaning robots working in semi-structured environments. In the literature, global path planning methods for free space usually focus on path length and neglect the traffic rule constraints of the environments, which leads to high-frequency re-planning and increases collision risks. In contrast, those for structured environments are developed mainly by strictly complying with the road network representing the traffic rule constraints, which may result in an overlong path that hinders the overall navigation efficiency. This article proposes a general and systematic approach to improve global path planning performance in semi-structured environments. A unidirectional road network is built to represent the traffic constraints in semi-structured environments and a hybrid strategy is proposed to achieve a guaranteed planning result. Cutting across the road at the starting and the goal points are allowed to achieve a shorter path. Especially, a two-layer potential map is proposed to achieve a guaranteed performance when the starting and the goal points are in complex intersections. Comparative experiments are carried out to validate the effectiveness of the proposed method. Quantitative experimental results show that, compared with the state-of-art, the proposed method guarantees a much better balance between path length and the consistency with the road network.