用超椭球与沃罗诺伊图结合，让机器人在狭窄通道中自动调整方向并安全通过。
Path Planning in Complex Environments with Superquadrics and Voronoi-Based Orientation
- 用超椭球扩展障碍物，消除不可通行区域。
- 沃罗诺伊超平面确保路径最大间距，提升通过率。
- 适合无人机、机械臂等需精准定向的复杂环境导航。
在迷宫和陷阱类复杂环境中，狭窄通道的路径规划极具挑战性，传统算法常因缺乏定向控制而失败。本文提出一种融合超椭球（SQ）表示与沃罗诺伊图的新方法，适用于2D与3D环境。该方法利用超椭球扩展障碍物，消除无法通行的区域；同时，沃罗诺伊超平面提供最大间距路径，并自然作为机器人姿态参考，使其长轴对齐通道方向。我们在2D物体抓取任务与3D无人机仿真中验证了该框架，结果表明其优于经典规划器及前沿无人机规划器，能确保可通行且具有最大安全距离的轨迹。
原文摘要 · Abstract (English)
Path planning in narrow passages is a challenging problem in various applications. Traditional planning algorithms often face challenges in complex environments like mazes and traps, where narrow entrances require special orientation control for successful navigation. In this work, we present a novel approach that combines superquadrics (SQ) representation and Voronoi diagrams to solve the narrow passage problem in both 2D and 3D environment. Our method utilizes the SQ formulation to expand obstacles, eliminating impassable passages, while Voronoi hyperplane ensures maximum clearance path. Additionally, the hyperplane provides a natural reference for robot orientation, aligning its long axis with the passage direction. We validate our framework through a 2D object retrieval task and 3D drone simulation, demonstrating that our approach outperforms classical planners and a cutting-edge drone planner by ensuring passable trajectories with maximum clearance.
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