%0 Journal Article
%T Dynamic trajectory planning for unmanned aerial vehicle based on sparse A* search and improved artificial potential field<br>基于稀疏A*搜索和改进人工势场的无人机动态航迹规划
%A YAO Yuan
%A ZHOU Xing-she
%A ZHANG Kai-long
%A DONG Dong
%A <br>姚远
%A 周兴社
%A 张凯龙
%A 董冬
%J 控制理论与应用
%D 2010
%I 
%X Based on the sparse A* search algorithm for path planning and the improved artificial potential field, we propose a method of dynamic trajectory planning for unmanned aerial vehicle(UAV) in the threat model composed of obstacles with different attributes. This method first builds a grid model of the threat distribution; and then, it makes the global path planning by sparse A* search algorithm according to the static obstacles; Finally, combining the pre-determined route and the dynamic obstacles, UAV can accomplish the dynamic trajectory planning by using the improved artificial potential field. Simulation results indicate that the proposed method can find a global optimal path with the given risk index and achieve a good performance of dynamic obstacle avoidance.
%K sparse A* search
%K trajectory planning
%K artificial potential field
%K dynamic obstacle avoidance<br>稀疏A*搜索
%K 航迹规划
%K 人工势场
%K 动态避障
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=461C79B6929715E9FA6D8A4E23CB98D3&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=DF92D298D3FF1E6E&sid=85A6AA3FF013E1BF&eid=4986C0B14AED27B4&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0