运动规划




运动规划（英语：Motion Planning）是一个过程，用来寻找从起始状态到目标状态的移动步骤。运动规划常常需要在运动受到约束的条件下找到最优解。运动规划多用于机器人学。


例如，一个清洁机器人在楼层里打扫卫生，它不能撞墙，也不能从楼梯口掉下去。给定一个任务，运动规划算法计算出一个动作序列，告诉机器人前进多少米，然后左转右转多少度。如果机器人要操作物品或者探测未知地形等等，运动规划就变得很复杂了。


除了机器人学，运动规划在计算机游戏里也用来模拟人物或车辆的运动。





概念




机器人所在的世界（英语：workspace）


基本的运动规划问题是通过连续的动作从起始位形s到达目标位形g，并且过程中要避开障碍物。机器人和障碍物可以抽象为二维或三维的几何图形，动作则被表示为位形空间中的路径。



自由空间




将世界抽象为位形空间，灰色区域表示障碍物，白色区域为自由空间（Cfree{displaystyle C_{free}}{displaystyle C_{free}}）。


如果机器人采用某个位形时不会碰到障碍物，那么这个位形属于自由位形空间，简称自由空间（英文写作Cfree{displaystyle C_{free}}{displaystyle C_{free}}）。自由空间的补集即障碍空间。


测试一个位形是否属于自由空间是简单的。先用正向运动学确定机器人的轮廓，然后查看机器人是否与障碍物碰撞。



算法


低维度的运动规划问题可以用基于格点的算法求解，如A*算法。







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