基于改进遗传算法的工厂AGV安全路径规划

为了避免危害事故的发生,在复杂的加工制造工厂中规划AGV小车安全无碰撞的行驶路径,不能简单地将AGV看成一个质点。首先在传统的障碍物栅格地图中叠加了环境安全信息,构建了融合信息栅格地图,提出了一种改进的遗传路径规划算法,在其适应函数中加入安全信息,并采用A*算法产生的初始路径为基准进行安全优化,减少了算法的搜索空间和复杂度。在MATLAB中对算法进行了验证,并在Gazebo中模拟了制造工厂AGV路径规划过程,验证了该方法具有较快的收敛速度及有效性。

Factory AGV Safety Path Planning Based on Improved Genetic Algorithm

In order to avoid the occurrence of hazardous accidents,planning the safe and collision-free driving path of AGV vehicles in complex manufacturing factories cannot simply regard AGV as a particle.First of all,an obstruction in the traditional grid map overlay the environmental safety information,build the information grid map,an improved genetic path planning algorithm is proposed,in its adaptive function to join the security information,and generate the initial path based on the A*algorithm optimization as a benchmark for security,reduce the search space and complexity of the algorithm.The algorithm is verified in MATLAB,and the AGV path planning process of the manufacturing plant is simulated in Gazebo,which verifies the convergence speed and effectiveness of the proposed method.