Real-time path planning with limited information for autonomous unmanned air vehicles
Automatica (Journal of IFAC)
Journal of Intelligent and Robotic Systems
Evolutionary path planner for UAVs in realistic environments
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Application of Improved Particle Swarm Optimization Algorithm in UCAV Path Planning
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
Evolutionary trajectory planner for multiple UAVs in realistic scenarios
IEEE Transactions on Robotics
Data Retrieving From Heterogeneous Wireless Sensor Network Nodes Using UAVs
Journal of Intelligent and Robotic Systems
Waypoint tracking of unmanned aerial vehicles using robust H2 / H? controller
International Journal of Systems, Control and Communications
Using genetic algorithms for navigation planning in dynamic environments
Applied Computational Intelligence and Soft Computing
On the performance comparison of multi-objective evolutionary UAV path planners
Information Sciences: an International Journal
Automation and Remote Control
Adaptive Dynamic Path Planning Algorithm for Interception of a Moving Target
International Journal of Mobile Computing and Multimedia Communications
3D Path Planning for Multiple UAVs for Maximum Information Collection
Journal of Intelligent and Robotic Systems
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Based on evolutionary computation, a novel real-time route planner for unmanned air vehicles is presented. In the evolutionary route planner, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is not required. The planner incorporates domain-specific knowledge, can handle unforeseeable changes of the environment, and take into account different kinds of mission constraints such as minimum route leg length and flying altitude, maximum turning angle, and fixed approach vector to goal position. Furthermore, the novel planner can be used to plan routes both for a single vehicle and for multiple ones. With Digital Terrain Elevation Data, the resultant routes can increase the surviving probability of the vehicles using the terrain masking effect.