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将机器人的工作空间和状态空间离散化为分层的位图与网格，利用波前扩展技术完成自由空间到低维骨架网络的快速收缩，并将路径规划的收缩法与势场函数相结合，形成完整的数值导航函数的计算方法。给出了快速收缩与导航函数计算的核心算法，以校园建筑物轮廓图为障碍空间，建立了具有扩展功能的平坦越野环境下的路径规划器。所附的仿真实例表明，该方法规划速度快，较好地解决了全局规划与局部规划的有机衔接，并可有效处理高维空间中多自由度机器人的运动规划问题。
The work space and state space of the robot are discretized into a hierarchical bitmap and a grid. The wavefront expansion technique is used to accomplish the rapid contraction of the free space to the low-dimensional skeleton network. The path planning shrinkage method is combined with the potential field function , Forming a complete numerical navigation function calculation method. The core algorithm of rapid contraction and navigation function calculation is given. Taking the contour map of campus buildings as the obstacle space, a path planner with extended functions under a flat cross-country environment is established. The attached simulation examples show that this method has a fast planning speed, better solves the organic connection between global programming and local programming, and can effectively deal with the motion planning problem of multi-degree-of-freedom robots in high-dimensional space.