This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three...This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three-dimensional space.The basic AP method has a shortcoming of easily plunging into a local optimal solution,which can result in navigation fails.To avoid the local optimum,we improved the AP method with a random scheme.In the improved AP method,random forces are used to make heterogeneous multi-UAVs/UGVs escape from local optimum and achieve global optimum.Experimental results showed that the improved AP method can achieve smoother trajectories and smaller time consumption than the basic AP method and basic potential field method(PFM).展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61273054,60975072)the National Basic Research Program of China("973" Project)(Grant No.2013CB035503)+3 种基金the Program for New Century Excellent Talents in University of China(Grant No.NCET-10-0021)the Top-Notch Young Talents Program of Chinathe Fundamental Research Funds for the Central Universities of Chinathe Aeronautical Foundation of China(Grant No.20115151019)
文摘This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three-dimensional space.The basic AP method has a shortcoming of easily plunging into a local optimal solution,which can result in navigation fails.To avoid the local optimum,we improved the AP method with a random scheme.In the improved AP method,random forces are used to make heterogeneous multi-UAVs/UGVs escape from local optimum and achieve global optimum.Experimental results showed that the improved AP method can achieve smoother trajectories and smaller time consumption than the basic AP method and basic potential field method(PFM).
