The Research On Path Planning For Autonomous Cross-Country Navigation Vehicle

Unmanned ground combat platform is running on the ground to carry out military tasks of the military component of the robot combat systems, and military unmanned ground vehicles is very important in unmanned combat platform, it could detect, attacks, and take other tasks .Autonomous Cross-Country Navigation Vehicle is a kind of unmanned military vehicles, environment sensing is the preparation of the path planning of ACCNV, to complete the work of the vehicle trajectory planning for the future of behavior control.The paper is focused on the cross-country environment obstacles World model and local and global path planning on simulation.In order to determine the relationship between the obstacles and ACCNV, we set up the certainty grid for obstacles. This paper explored the use of VFH (vector field histogram) and its improved algorithm for the path planning of ACCNV:1 According to certainty grid for obstacle world, the paper employs a two-stage data reduction technique, first of all, data reduction and the establishment of histogram grid, setting up a window. The window is mapped to one-dimensional histogram, it moves with the vehicle, the contents of each active cell in the histogram grid are now treated as an obstacle vector, the direction of which is determined by the direction from the cell to the vehicle centre point.2 Second data reduction and steering control. Two types of valleys are distinguished, namely, wide and narrow ones. Give the definition of wide and narrow valleys.3 The threshold .Choosing the proper threshold is critical issue, it can determine the direction.But vehicle shocks when it in a lot of obstacles, so, the VFH+ method is the result of several improvements over the original VFH method. By using a threshold hysteresis, the vehicle trajectory become more reliable and smoother, it explicitly takes into account the robot width. This method is also applied in the simulation of ACCNV path planning. VFH+ method is similar to the VFH method, read information from local environmental maps, decide direction of vehicle by histogram and cost function. It do a good job in the local path planning .Ant Colony Optimization is another global path planning method, the typical problem-TSP problem. We can analyze the advantages and disadvantages of establishing application ACO global path planning.In this paper, the cross-country map is based on graph search model, plans to use direction graph search to find the objective, corresponding to the certainty grid maps and the logic of the maps, we describe the model as the grid nodes, and using the heuristic search to find the shortest path in the global environment on the cross-country map.According to the results of the heuristic iterative, we can find a shortest path, but the time is not the shortest, then we make a discussion about heuristic parametersα,β, different values were discussed.As in the actual environment of most of them are cross-country and the whole combination of local path planning, path planning to take effective measures, the paper VFH method and its improved algorithm and the ant colony algorithm path planning is of important significance. The paper is about the research on path planning for autonomous cross-country navigation vehicle, it costs so much time and energy on the setting a model and simulation analysis, and gets the satisfactory outcome, so it is proved worthiness. The research of technology of ACCNV path planning is a huge and complex subject, and it needs a great deal of experiments and precise ponder. I just do my best work in my master's term, and the shortages can't be avoided. I hope my research and paper could provide material and some methods to the studying and the ones would study it in this area. This subject will be more and more perfect surely, I believe.