To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.Fir...To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.展开更多
Car routing solutions are omnipresent and solutions for pedestrians also exist.Furthermore,public or commercial buildings are getting bigger and the complexity of their internal structure has increased.Consequently,th...Car routing solutions are omnipresent and solutions for pedestrians also exist.Furthermore,public or commercial buildings are getting bigger and the complexity of their internal structure has increased.Consequently,the need for indoor routing solutions has emerged.Some prototypes are available,but they still lack semantically-enriched modelling (e.g.,access constraints,labels,etc.) and are not suitable for providing user-adaptive length-optimal routing in complex buildings.Previous approaches consider simple rooms,concave rooms,and corridors,but important characteristics such as distinct areas in huge rooms and solid obstacles inside rooms are not considered at all,although such details can increase navigation accuracy.By formally defining a weighted indoor routing graph,it is possible to create a detailed and user-adaptive model for route computation.The defined graph also contains semantic information such as room labels,door accessibility constraints,etc.Furthermore,one-way paths inside buildings are considered,as well as three-dimensional building parts,e.g.,elevators or stairways.A hierarchical structure is also possible with the presented graph model.展开更多
基金Project(60925011) supported by the National Natural Science Foundation for Distinguished Young Scholars of ChinaProject(9140A06040510BQXXXX) supported by Advanced Research Foundation of General Armament Department,China
文摘To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.
基金the Chair of GIScience,University of Heidelberg and the Klaus-Tschira Foundation (KTS) Heidelberg
文摘Car routing solutions are omnipresent and solutions for pedestrians also exist.Furthermore,public or commercial buildings are getting bigger and the complexity of their internal structure has increased.Consequently,the need for indoor routing solutions has emerged.Some prototypes are available,but they still lack semantically-enriched modelling (e.g.,access constraints,labels,etc.) and are not suitable for providing user-adaptive length-optimal routing in complex buildings.Previous approaches consider simple rooms,concave rooms,and corridors,but important characteristics such as distinct areas in huge rooms and solid obstacles inside rooms are not considered at all,although such details can increase navigation accuracy.By formally defining a weighted indoor routing graph,it is possible to create a detailed and user-adaptive model for route computation.The defined graph also contains semantic information such as room labels,door accessibility constraints,etc.Furthermore,one-way paths inside buildings are considered,as well as three-dimensional building parts,e.g.,elevators or stairways.A hierarchical structure is also possible with the presented graph model.
