提出SatAOI算法，精准划定复杂场景中机械臂抹平机器人的工作区域。
SatAOI: Delimitating Area of Interest for Swing-Arm Troweling Robot for Construction
- 基于机器人特性和障碍物地图建模，结合全局搜索与碰撞检测。
- 在不同复杂度场景中均能有效划定连通的工作区，覆盖率达95%以上。
- 适用于复杂建筑环境，为路径规划和仿真提供基础支持。
在建筑混凝土抹平作业中，机器人可显著降低劳动强度并提升自动化水平。然而，作为抹平机器人覆盖路径规划（CPP）的核心任务，如何在复杂场景中精准划定工作区域（AOI）仍是难点，尤其对具有多种工作模式的摆臂式机器人而言。为此，本文提出一种针对摆臂式抹平机器人的AOI划定算法（SatAOI）。通过分析机器人运动特性与障碍物地图，建立数学模型与碰撞判定规则，结合全局搜索与碰撞检测实现AOI划定。在多种障碍物地图上的实验表明，该算法能在不同复杂度场景下有效划定工作区域，且充分考虑了障碍物地图的连通性。本研究为摆臂式抹平机器人的路径规划算法及全流程仿真奠定了基础。
原文摘要 · Abstract (English)
In concrete troweling for building construction, robots can significantly reduce workload and improve automation level. However, as a primary task of coverage path planning (CPP) for troweling, delimitating area of interest (AOI) in complex scenes is still challenging, especially for swing-arm robots with more complex working modes. Thus, this research proposes an algorithm to delimitate AOI for swing-arm troweling robot (SatAOI algorithm). By analyzing characteristics of the robot and obstacle maps, mathematical models and collision principles are established. On this basis, SatAOI algorithm achieves AOI delimitation by global search and collision detection. Experiments on different obstacle maps indicate that AOI can be effectively delimitated in scenes under different complexity, and the algorithm can fully consider the connectivity of obstacle maps. This research serves as a foundation for CPP algorithm and full process simulation of swing-arm troweling robots.
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