基于改进人工势场法的医疗配送机器人路径规划

随着科技的高速发展和近几年新冠疫情的影响，医疗配送机器人开始逐步出现在各大医疗机构中，然而传统医疗配送机器人在使用人工势场算法进行路径规划时存在局部最优解和目标不可达问题。因此，针对局部最优解问题，提出了设计虚拟目标点的方法，将机器人从局部最优状态解救出来；针对目标不可达问题，在障碍物斥力势场函数中引入了目标距离函数对障碍物斥力进行限制，从而解决目标不可达问题。最后将该方法在多种复杂环境中与传统算法进行比较验证，实验结果表明，该改进算法能够解决传统算法存在的局部最优解和目标不可达问题，在算法效率上也提高了5%～9%,并且能够有效运用于实际场景。

Path planning of medical delivery robot based on improved artificial potential field method

With the rapid development of science and technology and the impact of the novel coronavirus epidemic in recent years, medical delivery robots have gradually appeared in major medical institutions. However, traditional medical delivery robots have local optimal solution problems and target unreachable problems when using artificial potential field algorithms for path planning. Therefore, for the local optimal solution problem, this paper proposed a method of designing virtual target points to rescue the robot from the local optimal state. It introduced the target distance function into obstacle repulsion potential field function to limit obstacle repulsion, to solve the problem of target unreachable. Finally, it compared the proposed method with the traditional algorithm in a variety of complex environments. The results show that the improved algorithm can solve the local optimal solution and target unreachable problems existing in the traditional algorithm, and the efficiency of the algorithm is also increased by 5%~9% and can be effectively applied to practical scenarios.