摘要
在建立并实现一种基于快速扩展随机树的机器人路径规划算法的仿真实验平台的基础上,通过该仿真实验平台所做的大量仿真实验表明:基于快速扩展随机树的路径规划算法具有强烈搜索未知空间的倾向,在各种障碍物环境下搜索出可达路径。该仿真实验平台运行稳定,功能完善,可直观地演示路径规划算法的搜索过程。
Rapidly-Exploring Random Trees (RRTs) was a randomized approach proposed in the end of 1990s, which can be applied in robot path planning and virtual reality. This paper establishes and realizes a simulation system for robot path planning based on RRTs. Many experiments on the simulation system show that the expansion of RRTs can be toward unexplored space, and the RRTs can find a path in variant obstacles. The simulation system runs stably, provides suitable operations, and intuitively shows the exploring process.
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2005年第2期86-92,共7页
Journal of Railway Science and Engineering
基金
国家自然科学基金资助项目(69975003)
中南大学博士论文创新选题基金资助项目(030618)
