Research on Hybrid A* and Genetic Algorithm for Path Planning

The field of intelligent robotics is progressing rapidly in today's rapid development of intelligence. Robots based on intelligent algorithms are being used in large numbers in various complex jobs to replace manual work, reduce human labor, and accomplish tasks more efficiently. In this paper, the real-life application of a warehouse robot walking is taken, avoiding obstacles and carrying items in a complex warehouse as the background. The job of a vehicle beginning from the starting point in a map with barriers and eventually reaching the end point is then realized in MATLAB using the A
^*
and genetic combination methods. The outcome of whether A
^*
is coupled with genetic algorithm in many instances can be determined through MATLAB operation and horizontal comparison. The results show that the algorithm can indeed carry out efficient global path planning, which can meet the practical application needs, and has certain application value and practicability. In the near future, path planning algorithms and intelligent robots will have rapid development, and both algorithmic control and hardware materials will be updated and iterated rapidly. The development trend of production intelligence and industrial wisdom all foretell that robots will become more and more intelligent and have more application scenarios in more fields to help humans or replace them in labor production. Path planning algorithms and intelligent robots will make people's lives more convenient, faster and better.