运动规划
工作区
计算机科学
动画
启发式
路径(计算)
碰撞检测
运动学
简单(哲学)
配置空间
树(集合论)
任意角度路径规划
平面图(考古学)
贪婪算法
机器人
计算机动画
算法
数学优化
碰撞
人工智能
计算机图形学(图像)
数学
哲学
数学分析
考古
物理
程序设计语言
认识论
历史
经典力学
量子力学
计算机安全
作者
James Kuffner,Steven M. LaValle
标识
DOI:10.1109/robot.2000.844730
摘要
A simple and efficient randomized algorithm is presented for solving single-query path planning problems in high-dimensional configuration spaces. The method works by incrementally building two rapidly-exploring random trees (RRTs) rooted at the start and the goal configurations. The trees each explore space around them and also advance towards each other through, the use of a simple greedy heuristic. Although originally designed to plan motions for a human arm (modeled as a 7-DOF kinematic chain) for the automatic graphic animation of collision-free grasping and manipulation tasks, the algorithm has been successfully applied to a variety of path planning problems. Computed examples include generating collision-free motions for rigid objects in 2D and 3D, and collision-free manipulation motions for a 6-DOF PUMA arm in a 3D workspace. Some basic theoretical analysis is also presented.
科研通智能强力驱动
Strongly Powered by AbleSci AI