Curves and surfaces for computer aided geometric design: a practical guide
Curves and surfaces for computer aided geometric design: a practical guide
MOPSO: a proposal for multiple objective particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Genetic algorithm based approach for Multi-UAV cooperative reconnaissance mission planning problem
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Evolutionary Route Planner for Unmanned Air Vehicles
IEEE Transactions on Robotics
Evolutionary algorithm based offline/online path planner for UAV navigation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Enhancing automated red teaming with evolvable simulation
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
DEVS/SOA: Towards DEVS Interoperability in Distributed M&S
DS-RT '09 Proceedings of the 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications
Evolutionary trajectory planner for multiple UAVs in realistic scenarios
IEEE Transactions on Robotics
Feasible UAV path planning using genetic algorithms and Bézier curves
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Application of multi-objective bee colony optimization algorithm to automated red teaming
Winter Simulation Conference
Multiple objective optimisation applied to route planning
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Evolving large scale UAV communication system
Proceedings of the 14th annual conference on Genetic and evolutionary computation
On the performance comparison of multi-objective evolutionary UAV path planners
Information Sciences: an International Journal
| Hi-index | 0.00 |
This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Evolutionary Algorithms (EA) that can be used in realistic risky scenarios. The path returned by the algorithm fulfills and optimizes multiple criteria which (1) are calculated based on properties of real UAVs, terrains, radars and missiles, and (2) are used to rank the solutions according to the priority levels and goals selected for each mission. Developed originally to work with only one UAV, the planner currently allows us to obtain the optimal path of several UAVs that are flying simultaneously. It works globally offline and locally online to recalculate a part of the path when an unexpected threat appears. Finally, the effectiveness of the solutions given by this planner has been successfully tested against a simulator that implements a complex model of the UAV and its environment.