Motion planning and navigation, especially for mobile robots operating in complex navigational environments, has been a central problem since robotics started. A heuristic way to address it is the construction of a graph-based representation (a path) capturing the connectivity of the configuration space. Probabilistic Roadmap is a commonly used method by the robotics community to build a path for navigational mobile robot path planning. In this study, path smoothening by arc fillets is proposed for mobile robot path planning after obtaining the path from PRM in the presence of the obstacle. The proposed method runs in two steps; the first one is generating the shortest path between the initial state to one of the goal states in the obstacle presence environment, wherein the PRM is used to construct a straight-lined path by connecting the intermediate nodes. The second step is smoothening every corner caused by node presence. Smoothening the corners with arc fillets ensures smooth turns for the mobile robots. The suggested method has been simulated and tested with different PRM features. Experiment results show that the constructed path is not just providing smooth turning; it is also shorter and quicker to finish for a robot while avoiding obstacles.
翻译:移动规划和导航,特别是对在复杂导航环境中运行的移动机器人而言,这是自机器人开始以来的一个中心问题。 解决它的一个杂乱无章的方法是构建基于图形的演示(路径),捕捉配置空间的连通性。 概率路线图是机器人社区常用的一种方法,用来构建导航移动机器人路径规划路径。 在这项研究中, 以弧填充物平滑路径, 在障碍状态下从 PRM 获得路径后, 被建议用于移动机器人路径规划。 提议的方法分两个步骤运行; 第一个步骤是在障碍存在环境中从初始状态到目标状态状态之一之间产生最短的路径, 在障碍存在环境中, PRM 用来通过连接中间节点来构建直线路径。 第二步是平滑每个角落。 用弧填充料滑动角可以确保移动机器人平稳旋转。 所建议的方法已经用不同的 PRM 特征进行了模拟和测试。 实验结果显示, 建造的路径不仅仅是提供平稳的转动; 它也缩短和更快地完成机器人, 同时避免障碍。