基于RRT*算法和多姿态碰撞检测的无人工地多机协同路径规划研究

Research on Multi-Machine Collaborative Path Planning for Unmanned Construction Sites Based on RRT* Algorithm and Multi-Posture Collision Detection

摘要

针对现有无人工地路径规划技术对施工设备几何与运动特征考虑不足，且缺乏多机协同机制的问题，提出一种基于改进RRT*算法的多机协同路径规划方法。首先，将行走设备在俯视平面内设定为具有普遍性的矩形，利用分离轴定理和向量叉积等手段提出了矩形设备在直线行进和旋转过程中与障碍物的碰撞检测方法；其次，引入时间窗机制与时空域协同规划框架，设计了“行进-行进”与“行进-旋转”两类动态冲突检测流程，解决了多设备协同作业中的即时避碰问题；最后，将该算法应用于隧道及梁场等复杂场景中进行仿真验证。结果表明：所提算法规划的路径考虑了真实设备的形状、尺寸、转向角约束以及障碍物的形状、尺寸、分布，相比传统算法，有效解决了大长宽比设备在狭长空间内的避障难题，显著提升了复杂受限环境下的路径搜索成功率与鲁棒性；另外构建的时空域协同规划框架确保了多设备在复杂工地环境中安全、有序、高效地行驶或作业；该研究不仅验证了算法在隧道、梁场等真实工程场景中的适用性，也为未来实现无人工地机群的智能化、高效化协同作业提供了重要的理论依据与技术支撑。

Abstract

To address the limitations of existing path-planning methods applied to unmanned construction site, particularly their insufficient consideration of equipment geometry and kinematic characteristics, as well as the absence of effective multi-machine coordination, this study proposes a cooperative path-planning approach based on an improved RRT* algorithm. First, mobile construction equipment is modeled as the generalized rectangle in the top-down plan, and collision-detection strategies for both linear motion and rotational motion are developed using the separating axis theorem and vector cross-product operations. Second, a time-window mechanism and a spatiotemporal coordination framework are introduced to design two types of dynamic conflict-detection procedures, namely “straight-line-straight-line motion” and “straight-line-rotation motion”, enabling real-time collision avoidance among multiple machines. Finally, the proposed algorithm is validated through simulations in complex scenarios such as tunnels and beam fabrication yards. The results demonstrate that the planned paths fully account for the actual equipment geometry, dimensions, rotation constraints, and obstacle characteristics (shape, size, and distribution). Compared with conventional algorithms, the proposed method effectively resolves the challenge of obstacle avoidance for large length-width ratio equipment operating in narrow spaces, significantly improving path-search success rates and robustness in complex environments. Furthermore, the constructed spatiotemporal collaborative planning framework ensures that multiple machines can safely, orderly, and efficiently move or operate in complex construction site environments. This research not only verifies the applicability of the algorithm in real engineering contexts, such as tunnels and beam yards, but also provides essential theoretical and technical support for future intelligent and efficient multi-machine collaboration in unmanned construction sites.

关键词

无人工地 / 路径规划 / 快速扩展随机树 / 碰撞检测 / 多机协同

Key words

unmanned construction site / path planning / rapidly-exploring random tree / collision detection / multi-machine collaboration

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基金资助

国家重点研发计划项目(2023YFB2603900)

江西省教育厅科学技术研究项目(GJJ2400506)

江西省职业早期青年科技人才培养项目(20244BCE52140)