基于深度值的虚拟人手臂运动规划

Motion planning for human arm based on depth buffer

提出了基于深度值(z-buffer值)的虚拟人手臂运动规划新方法,将路径规划算法———A*算法扩展到三维空间,并利用图形硬件获得的深度值进行碰撞检测,解决了受限空间的运动规划问题。仿真结果显示,能快速有效的实现虚拟人手臂7个自由度的运动规划。

This dissertation proposed a new motion planning algorithm for human arm based on depth buffer （z-buffer）. This method expanded the A ＊ algorithm to three-dimensional space and detected collision taking advantage of a special computer graphics hardware-depth buffer. Thus it was addressed the problem of confined space motion planning for human arm. The simulation results show that this algorithm can realize the motion planning for a human arm with 3 links and 7 DOFs rapidly and effectively.