Path planning of agricultural mobile robot based on hybrid improved sparrow search algorithm
Aiming at the shortcomings of current agricultural mobile robot path planning methods that are prone to produce a local optimal path,a mobile robot path planning algorithm based on hybrid multi-strategy improved sparrow search algorithm is proposed.Firstly,for improving the optimizing ability of sparrow search algorithm,the even symmetric infinite folding chaotic sequence,spiral search finder update,multiple learning follower update are introduced to improve the population diversity,search blindness and global search ability of the traditional algorithm,so as to realize the Multi-Strategy Hybrid Improved Sparrow Search Algorithm(MHISSA).Then,the path planning model of mobile robot is constructed,and the coding method of population individuals is defined by using the navigation point model,and the fitness function of synchronous obstacle avoidance and shortest path is constructed.Combined with cubic spline interpolation,MHISSA algorithm is applied to solve the global path planning problem of mobile robot.Simple and complex obstacle environments are constructed,and the experimental comparative analysis of single robot path planning and multi-robot cooperative path planning are carried out.The results show that the improved algorithm can get a smooth and collision-free optimal path,the optimal value and the average value of path planning length are 23.08%and 19.56%lower than those of the traditional sparrow search algorithm respectively.The field scene case verification proves that the method has good practicability in the field of path planning for agricultural mobile robots.
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