Research On Small Body Observing Planning Of 3D Modeling

The exploration of small celestial bodies can effectively improve the level of deep-space exploration technology in China and promote the development of planetary science.Three-dimensional modeling of small bodies is an important part of deep space exploration.The 3D modeling of small celestial bodies requires a large amount of image data with high resolution.On the one hand,the detector will make frequent orbital maneuvers to capture enough images,and on the other hand,the data transmission time of the detector will be increased.Therefore,it is an important technical link of 3D modeling of small bodies to carry out observation task planning and save fuel and communication resources of detectors as much as possible under the premise of meeting the demand of 3D modeling image data of small bodies.The process of small celestial body detection mission is from far to near,which can be summarized as "long distance observation--modeling--low resolution modeling--close observation--modeling--high resolution modeling".Based on the principle of stereophoto 3D modeling of small celestial bodies,this paper extracts the constraint conditions of photometric 3D reconstruction method for imaging observation,and uses genetic algorithm to plan the close-range observation scheme according to the low-resolution 3D model of remote observation.The main research contents of this paper include:(1)In this paper,genetic algorithm is used to solve the problem of observation planning for 3D modeling of small celestial bodies.Based on the basic principle of photometric three-dimensional reconstruction method and the actual demand of observation planning scheme,the observation planning scheme is abstracted into a combinatorial optimization problem of observation position and observation movement,and the observation position and observation movement of the detector are designed in the simulation environment.The genetic algorithm is designed and implemented to solve the combinatorial optimization problem of observation planning,and the results of observation planning scheme are verified by experiments.The experimental results show that the observation planning scheme obtained by using genetic algorithm is correct and effective.(2)In this paper,a robust genetic algorithm(GA)observation planning method is proposed to study the influence of the interference factors such as the position,direction and vibration of the probe on the stability of observation planning results in the deep space exploration environment.The Monte Carlo resampling method was designed and the robustness constraint condition was added to improve the stability of the observation planning method based on genetic algorithm in the complex environment of deep space exploration,and the influence of disturbance factors on the observation planning method was reduced.The comparative experimental analysis was carried out to verify the effectiveness of the method.The small celestial body 3D modeling observation planning method proposed in this paper effectively improves the observation efficiency in the surveying and mapping process of small celestial bodies.On the premise of meeting the requirements of 3D reconstruction of small celestial bodies,the number of detector maneuvers is reduced and the transmission amount of image data is reduced.