Research on path planning of electric tractor based on improved ant colony algorithm

The emergence of electric tractors and related control technologies has accelerated the development of modern agriculture, but the path planning problem of electric tractors affects their operating range to a certain extent. In this paper, an improved ant colony algorithm is proposed to address the problems that the basic ant colony algorithm in the path planning of electric tractors is prone to local optimal solutions and slow convergence speed. Based on the idea of "Newton's cooling law", the pheromone volatility factor and state transfer probability function are improved to enhance the ability of global search in the early iteration of the algorithm and accelerate the convergence speed in the middle and late iteration; the early termination strategy of the algorithm iteration is introduced to reduce the iteration redundancy and shorten the running time of the algorithm; based on the kinematic model of the electric tractor, a mathematical model of energy loss is established to shorten the running time of the algorithm. Based on the kinematic model of electric tractor, the mathematical model of energy loss is established, and the evaluation index of the optimal path is established. The simulation results show that compared with the literature algorithm and the basic ant colony algorithm, the energy loss of the electric tractor is reduced by 18.31% and 28.96%, the optimal path length is shortened by 0.81% and 0.97%, and the running time is reduced by 20.13% and 18.43%, respectively. The comprehensive performance of the improved algorithm in this paper is excellent, which verifies the optimization effect.