Path planning for multiple unmanned aerial vehicles by parameterized Cornu-Spirals
ACC'09 Proceedings of the 2009 conference on American Control Conference
ACC'09 Proceedings of the 2009 conference on American Control Conference
Multiple UAV path planning using anytime algorithms
ACC'09 Proceedings of the 2009 conference on American Control Conference
UAV Path Planning Based on Bidirectional Sparse A* Search Algorithm
ICICTA '10 Proceedings of the 2010 International Conference on Intelligent Computation Technology and Automation - Volume 03
An Improved Heuristic Algorithm for UAV Path Planning in 3D Environment
IHMSC '10 Proceedings of the 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 02
A genetic-algorithm-based approach to UAV path planning problem
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Path Planning Strategies for UAVS in 3D Environments
Journal of Intelligent and Robotic Systems
Evolutionary Route Planner for Unmanned Air Vehicles
IEEE Transactions on Robotics
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Most of the 3D curve path planning is used to build static path planning. For intercepting of a moving target, the path planning has to be set in a dynamic condition. L+Dumo algorithm which is based on curve is used to intercept a moving target. In the real situations, the Unmanned Aerial Vehicle UAV has possibility to intercept a moving target from all direction. It is assumed that environment of the UAV is in 3D Euclidean Space. It means that the UAV has to adapt for all quadrants for interception of a moving target. This research develops a path planning algorithm which enhances the previous L+Dumo algorithm to encounter the possibility quadrants. The enhancement would be simulated in C++ language to determine the accuracy of the algorithm. The simulation is conducted using one UAV and one moving target with random obstacles of cylindrical shape in between both objects. The result shows that the system accuracy is 81.0876%, a level which is able to encounter all possibility quadrants.