中文摘要：

为了克服人工势场法的缺陷、提高其路径规划性能，提出了改进的人工势场法。分析了人工势场法原理，针对其目标不可达问题，将机器人与目标点距离引入到斥力场函数，得到了改进的斥力场函数；针对局部最小值问题，引入逃逸力；为进一步提高算法性能，使用遗传算法优化参数设置，使得规划路径更加平滑；根据环境复杂度，提出了自适应步长调节算法。使用仿真实验对改进算法进行了验证，结果表明，改进算法可以克服传统算法目标不可达、局部最小值问题，而且改进算法路径更加平滑，自适应步长算法在路径规划中行走61步到达目标，固定步长法行走145步到达目标，充分说明了改进算法的优越性。

英文摘要：

To overcome shortcomings of artificial potential field and improve its property, improved artificial potential field algorithm is proposed. By analyzing principle of artificial patential field, for the problem that goal cannot achieve, distance of robot and goal is introduced to repulsion field function, so that improved repulsion field function is gatten. For the problem of local minima, escape force is introduced. To advance property of the algorithm, genetic algorithm is used to optimize parameters, which makes the path smooth. According to complexity of working area, adaptive step is put forward. Simulation trial is performed to clarify the improved algorithm, the improced algorithm can overcome problems that goal cannot achieve and local minimca The robot walks 61 steps by method of adaptive step length, and 145 steps by fix step length.