机器人Issue(4)：443-450,8.DOI:10.13973/j.cnki.robot.2015.0443
复杂环境下基于RRT的智能车辆运动规划算法
RRT-based Motion Planning Algorithm for Intelligent Vehicle in Complex Environments
摘要
Abstract
The existing planning algorithms can not properly solve the motion planning problem of intelligent vehicle in complex environments with many irregular and random obstacles. To solve the problem, a simple and practical RRT-based algorithm, continuous-curvature RRT algorithm, is proposed. This algorithm combines the environmental constraints and the constraints of intelligent vehicle with RRTs. Firstly, a goal-biased sampling strategy and a reasonable metric function are introduced to greatly increase the planning speed and quality. And then, a post-processing method based on the max-imum curvature constraint is presented to generate a smooth, continuous-curvature and executable trajectory. Simulation experiments and real intelligent vehicle test verify the correctness, validity and practicability of this algorithm.关键词
运动规划/智能车辆/快速搜索随机树/曲率约束Key words
motion planning/intelligent vehicle/RRT (rapidly-exploring random tree)/curvature constraint分类
信息技术与安全科学引用本文复制引用
杜明博,梅涛,陈佳佳,赵盼,梁华为,黄如林,陶翔..复杂环境下基于RRT的智能车辆运动规划算法[J].机器人,2015,(4):443-450,8.基金项目
国家自然科学基金重大研究计划重点项目（91120307）；国家自然科学基金重大研究计划集成项目（91320301）；国家自然科学基金青年基金资助项目（61304100）． （）
