Field Complete Coverage Path Planning Based on Improved Genetic Algorithm for Transplanting Robot

The Complete Coverage Path Planning (CCPP) is a key technology in the field of agricultural robots, and has great significance for improving efficiency quality tillage, fertilization, harvesting, other robot operations, as well reducing operation energy consumption. traditional boustrophedon- or heuristic-search-algorithm-based CCPP methods, when coping with irregular boundaries, obstacles, complex environments, still face many problems challenges, such large repeated work areas, multiple turns U-turns, low efficiency, prone to local optimum. In order solve above problems, an improved-genetic-algorithm-based method was proposed this paper, innovatively extends genetic algorithm’s chromosomes single-point mutation into chromosome pairs multi-point mutation, multi-objective equilibrium fitness function. simulation experimental results on simple regular fields showed that achieved comparable performance boustrophedon-based method. However, fields, reduces 38.54% area 35.00% number can save 7.82% consumption average. This proved strong adaptive capacity environment, practical application value machinery