Global path planning and local obstacle avoidance of searching robot in mine disasters based on grid method

Aiming at the uncertainty of the environment in mine disasters, the gird model was built based on the GIS (geographic information system) map acquired from the mine in advance, and a modified genetic algorithm was provided for global path planning. An efficient method for population initialization which adopted the position information negative feedback like the ant colony optimization and priority grouping was provided. Also the population initialization method was applied to the mutation operator. The method self-adaptively adjusted the probabilities of crossover and mutation due to the change of the best resolution. According to the condition of the environment and combining with the global path planning result a local obstacle avoidance method was presented. Finally, the simulation results verify that the provided method can provide an optimal path in known environment effectively, and reallize the real time obstacle avoidance in locally changed environment.