摘要
研究复杂环境下虚拟人的装配拆卸路径问题,为提高规划效率,提出了一种基于快速扩展随机树(RRT)的高维空间路径规划算法。首先根据虚拟人装配操作中关节的优先度对C空间进行了分解,然后在此基础上提出了一种基于子空间的增量采样策略,并对路径规划过程中虚拟人与装配体以及虚拟人自身关节的碰撞检测过程进行了优化。为检验算法有效性,构建了一个复杂环境下虚拟人移出装配体的实例,实验结果显示,改进算法有效提高了虚拟人的产品零部件装配拆卸路径规划效率。
Aiming at the virtual human- based assembly (disassembly) path planning in the complex environment, a RRT-based path planning algorithm in high dimensional space was presented. Firstly, this algorithm was used to decompose C-space according to the priority of virtual human's joints about assembly process. And then an incremental sampling method was constructed based on the C-space decomposition. The self collision detection of vir- tual human parts and the collision between virtual human and assemblies were also optimized. For testing the effec- tiveness of the algorithm, a part disassembly example in a complex environment was constructed. The experimental results show that the algorithm is effective to improve the efficiency of virtual human-based path planning.
出处
《计算机仿真》
CSCD
北大核心
2014年第5期423-427,共5页
Computer Simulation
关键词
路径规划
虚拟人
空间分解
Path planning
Videoirtual human
C-space decomposition