Path planning of unmanned aerial vehicle based on improved gravitational search algorithm  

作　　者：LI Pei DUAN HaiBin 

机构地区：[1]Science and Technology on Aircraft Control Laboratory,School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China [2]State Key Laboratory of Virtual Reality Technology and Systems,Beihang University,Beijing 100191,China

出　　处：《Science China(Technological Sciences)》2012年第10期2712-2719,共8页中国科学（技术科学英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos. 60975072,60604009);the Program for New Century Excellent Talents in University of China (Grant No. NCET-10-0021);the Aeronautical Foundation of China (Grant No. 20115151019);the Fundamental Research Funds for the Central Universities of China

摘　　要：Path planning of Uninhabited Aerial Vehicle(UAV) is a complicated global optimum problem.In the paper,an improved Gravitational Search Algorithm(GSA) was proposed to solve the path planning problem.Gravitational Search Algorithm(GSA) is a newly presented under the inspiration of the Newtonian gravity,and it is easy to fall local best.On the basis of introducing the idea of memory and social information of Particle Swarm Optimization(PSO),a novel moving strategy in the searching space was designed,which can improve the quality of the optimal solution.Subsequently,a weighted value was assigned to inertia mass of every agent in each iteration process to accelerate the convergence speed of the search.Particle position was updated according to the selection rules of survival of the fittest.In this way,the population is always moving in the direction of the optimal solution.The feasibility and effectiveness of our improved GSA approach was verified by comparative experimental results with PSO,basic GSA and two other GSA models.

关 键 词：uninhabited aerial vehicle path planning gravitational search algorithm social information weighted value selection rules 

分 类 号：O314[理学—一般力学与力学基础] TP18[理学—力学]