结合模糊决策与势场栅格的智能小车路径规划

Intelligent Car Path Planning with Fuzzy Decision and Potential Grid Method

针对智能小车在路径规划过程中环境建模和人工势场法存在的问题,建立了栅格法与势场法相结合的路径规划方法,并对结合后的势场栅格路径规划方法的缺陷和不足进行了改进。首先,在斥力场函数中引入影响因子,促使在目标点附近的斥力场能够迅速减小,从而解决障碍物附近目标不可达和振荡的问题;其次,将模糊决策和势场栅格法进行有机结合,考虑航向角,建立了势场值和航向角的隶属度函数,选择隶属度函数值最大的栅格作为路径点,有效地提高了路径的平滑性。论文通过matlab对改进前后的算法进行了仿真实验,结果表明该方法实时性好,路径平滑,充分体现了其有效性和优越性。

In order to overcome the problems of environment modeling and potential field method in the path planning of intelligent car,the path planning method combining the grid method and the potential field method is established,and the deficiencies and shortcomings with potential grid path planning method was improved.Firstly,a influence factor is introduced into the repulsive field function,promote the repulsion field near the target point can decrease rapidly,and the problem of target unreachable and oscillating can be solved.Secondly,the fuzzy decision and potential grid method are combined organically,introducing the course angle,establishing the field value function and membership function,choosing the maximum membership function value as path point,thus can improve the smoothness of the path effectively.The simulation and contrast experiments of the improved algorithm are carried out by matlab.The results show that the method is real-time and smooth,which fully demonstrates the effectiveness and superiority of it.