Research On Path Planning Of Lunar Surface Detector Under Multi-Objective Constraints

The use of moving detectors to detect the surface of the moon is the mainstream means for the major space powers to carry out lunar exploration.The mobile ability of the lunar surface detector is the guarantee to complete all kinds of scientific experiments(lunar rock detection,lunar soil sampling,etc.),and the quality of its path planning will affect the efficiency of the detection task.In the path planning of lunar surface detector,the constraints such as slope,roughness and fluctuation will affect the climbing ability,multi wheel coordinated control ability(driving ability)and obstacle surmounting ability of lunar surface detector;the length,smoothness and safety of the path will determine the quality of the path.Based on a pre research project of manned spaceflight,this paper takes the lunar probe as the research object,and studies the modeling of lunar environment and the path planning method of lunar probe in the process of detecting mission.The main research work is as follows:(1)An environment modeling method based on multi constraint path planning is improved.Based on the three-dimensional model of lunar surface generated by digital elevation map,the structure characteristics of lunar surface detector are analyzed,and the lunar surface terrain information factors are extracted.The three terrain information factors of the lunar surface environment,i.e.the terrain slope,roughness and undulation,are taken as the environmental constraints to construct the passable cost function of the full-term lunar surface detector's moving conditions,so as to solve the passable cost function of lunar surface detector Row area and construct the corresponding grid map.(2)Global path planning based on improved ant colony algorithm.According to the known environmental information,the grid method is used to model the environment,and the ant colony algorithm is used to search the path.In order to solve the problem of using path length as the evaluation index in the global path planning method,the constraint indexes of path length,smoothness and security are considered in the path evaluation,and the comprehensive evaluation function is obtained by linear weighting.The strategies of two-way parallel search,adaptive adjustment of state transfer,pheromone volatilization factor and reprocessing of inflection point are introduced to solve the original problem Ant colony algorithm is easy to fall into the problem of local optimum and slow convergence.(3)Local path planning based on improved dynamic window method.The dynamic window method considers the dynamic performance of the robot.In view of the structural performance of the lunar surface detector itself,the steering angle constraint is introduced and the evaluation function is improved,so that the detector can avoid obstacles in real time when the environmental information is unknown,improve the comprehensive ability of the detector for path selection,and improve the speed control ability of the detector when it is walking.(4)Integrated path planning based on improved ant colony algorithm and dynamic window method.Local path planning is carried out along the nodes of global path,so as to realize the close combination of global path planning and local path planning.Even if there is a sudden change in the environment,the detector can reach the target successfully.In this thesis,the specific implementation process of path planning integration optimization is given,and simulation experiments are designed on MATLB platform to verify the effectiveness of the integrated path planning method.