The Research Of Lunar Rover Path Planning With Human-machine Collabrative

Lunar rover path planning is a critical technology of the lunar rover exploration in the complex lunar environment. It directly affects the energy consumption of the lunar rover, time consuming and associated performance. Path planning is mostly independent roaming, from the perspective of artificial intelligence,rarely consider the human intelligent. In this paper, on the basis of artificial intelligence path planning, adding the man-machine cooperation related to technology,optimizes the aitificial path planning technology.This paper based on the the ant colony algorithm,proposes four improvement strategies to solve the pratical problems in the lunar rover path planning and then proposes a lunar rover artificial path planning method. Effectiveness and accurateness of the algorithm was verified through simulation experiments. This method can quickly plan a collision-free path of primaries.This paper bases on the collision-free path through the improved ant ant colony algorithm. Joined the extraction of3D terrain information and more impaired rover mechanical analysis,further considering the more impaired ability of the lunar rover path planning. Through simulation and laboratory experiments, certify the lunar rover Obstacle standards. Based on this standard,this paper use dynamic focusing method to modify the path in the local area which across the way for the lunar rover can cross the obstacle.Finally determine a selective obstacle optimal path.Finally,this paper propose a lunar rover path planning method with human machine collaborative In this method,the artificial planning path can be further optimized,the advantages of the machine in the data processing and human experience-oriented to come together as one and lunar rover on the basis of driving safety tends to be more rapid and reasonable.Meanwhile this paper propose a path planning passing assessment method based on the thesis of Multi-attribute TOPSIS to assess the quality of the planned path,and the experimental results show that the proposed method is effective and practical.