Path planning of intelligent information acquisition robot in planted forest

Considering the path planning issue of an intelligent motion robot which will be used to acquire environment information and tree growing information in a planted forest, a kind of improved genetic algorithm based path optimization method is proposed. According to tree´s distribution style in a planted forest the robot´s working environment is modeled as many grids which are labeled either ordered couples or sequence numbers. Then how to initialize the population is introduced and the fitness function to optimize the motion path of an information acquiring robot in a planted forest is defined. Some genetic operators, such as selection operator, crossover operator and mutation operator, are designed and a kind of operator to detect redundant grids is put forward. The simulation under the VC++ Platform is carried out. The result indicates that the proposed algorithm is efficient way to plan a optimal path for the information acquiring motion robot in a planted forest.