提出单向路网规划法,兼顾路径短与交通规则一致
Unidirectional-Road-Network-Based Global Path Planning for Cleaning Robots in Semi-Structured Environments
- 构建单向路网表示半结构化环境交通约束
- 允许起点终点跨路连接,路径更短
- 双层势场图保障复杂路口规划可靠性
清洁机器人在半结构化环境中实现高效全局路径规划是商业化关键。现有方法中,自由空间规划侧重路径长度,忽略交通规则,导致频繁重规划和碰撞风险;而结构化环境方法严格遵循道路网络,常生成过长路径,降低导航效率。本文提出一种通用系统性方法,构建单向路网以表征半结构化环境的交通约束,并采用混合策略保证规划结果。允许在起始点和目标点处跨越道路,以获得更短路径。特别地,提出两层势场图,在起终点位于复杂交叉口时仍能保证规划性能。对比实验验证了该方法的有效性。定量结果表明,相比当前最优方法,本方法在路径长度与道路网络一致性之间实现了更好平衡。
原文摘要 · Abstract (English)
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.
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