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 represent- ing 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 pote- ntial map is proposed to achieve a guaranteed performance when the starting and the goal points are in complex intersect- ions. Comparative experiments are carried out to validate the effectiveness of the proposed method. Quantitative experimen- tal results show that, compared with the state-of-art, the propo- sed method guarantees a much better balance between path length and the consistency with the road network.