基于平面简化路径规划，让机器人在复杂建筑中高效顺畅行走
Efficient Trajectory Generation Based on Traversable Planes in 3D Complex Architectural Spaces
- 将可通行区域抽象为平面图，降低三维空间复杂度
- 实测在仿真与真实机器人上均实现平滑高效轨迹生成
- 适合需在多层建筑中自主导航的地面机器人使用
随着机器人融入人类生活，其在人们主要活动的建筑空间中的作用日益突出。尽管机器人运动能力与精确定位技术迅速发展，但在复杂多层建筑环境中生成高效、平滑、完整且高质量的轨迹仍是挑战。本文提出一种新型高效规划算法，使地面机器人能在大型复杂多层建筑空间中自主导航。考虑到可通行区域通常包含地面、斜坡和楼梯，这些结构大多为平面或近似平面，因此将问题简化为在复杂相交平面间进行导航。首先通过分割、合并、分类与连接从3D点云中提取可通行平面，构建轻量但完整的平面图；随后基于运动状态轨迹进行优化，并充分考虑跨多层平面时的特殊约束，以最大化机器人的机动性。我们在模拟环境和真实场景下的CubeTrack机器人上进行了实验，验证了该方法的有效性与实用性。
原文摘要 · Abstract (English)
With the increasing integration of robots into human life, their role in architectural spaces where people spend most of their time has become more prominent. While motion capabilities and accurate localization for automated robots have rapidly developed, the challenge remains to generate efficient, smooth, comprehensive, and high-quality trajectories in these areas. In this paper, we propose a novel efficient planner for ground robots to autonomously navigate in large complex multi-layered architectural spaces. Considering that traversable regions typically include ground, slopes, and stairs, which are planar or nearly planar structures, we simplify the problem to navigation within and between complex intersecting planes. We first extract traversable planes from 3D point clouds through segmenting, merging, classifying, and connecting to build a plane-graph, which is lightweight but fully represents the traversable regions. We then build a trajectory optimization based on motion state trajectory and fully consider special constraints when crossing multi-layer planes to maximize the robot's maneuverability. We conduct experiments in simulated environments and test on a CubeTrack robot in real-world scenarios, validating the method's effectiveness and practicality.
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