Path planning plays an important role while moving the robot from one location to another. The present paper is concerned with solving the path planning problem of the biped robot in a static environment. Here, an attempt is made to combine the benefits of established rapidly exploring random trees (RRT) algorithm and visibility graph algorithm. Various approaches, such as normal RRT that starts the search from start and goal points, multi-node point RRT approach in which a random node is generated somewhere in between the start and goal points, and a tree is started from each of these points as the root, has been developed. Further, visibility graph has also been applied to smooth or optimize the path obtained in the previous step. The developed path planning algorithms are initially tested in computer simulations. For experimental purposes, a global camera attached at the top of the terrain is used to map the environment. Further, a humanoid with 18 degrees of freedom is used to execute the path decided by the algorithm. Required corrections are made at regular intervals if the robot deviates from its path.

在将机器人从一个位置移动到另一个位置时，路径规划起着重要作用。本论文涉及解决静态环境下双足机器人的路径规划问题。在这里，尝试结合已建立的快速探索随机树 (RRT) 算法和可见性图算法的优点。各种方法，例如从起点和目标点开始搜索的普通 RRT，多节点点 RRT 方法，其中在起点和目标点之间的某处生成随机节点，并且从这些点中的每一个点开始一棵树作为根，已经开发。此外，还应用了可见性图来平滑或优化上一步中获得的路径。开发的路径规划算法最初在计算机模拟中进行测试。出于实验目的，连接在地形顶部的全局相机用于映射环境。此外，使用具有 18 个自由度的仿人机器人来执行算法决定的路径。如果机器人偏离其路径，则会定期进行所需的更正。