IBM Journal of Research and Development
Hermite interpolation by Pythagorean hodograph quintics
Mathematics of Computation
Introduction to Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots
Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle
ICHIT '06 Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02
Planning Algorithms
Multiple path coordination for mobile robots: a geometric algorithm
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
The elastic bending energy of pythagorean-hodograph curves
Computer Aided Geometric Design
Abstraction and control for Groups of robots
IEEE Transactions on Robotics
UAV bezier curve maneuver planning using genetic algorithm
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Meshing and Simplification of High Resolution Urban Surface Data for UAV Path Planning
Journal of Intelligent and Robotic Systems
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This paper presents a methodology based on a variation of the Rapidly-exploring Random Trees (RRTs) that generates feasible trajectories for a team of autonomous aerial vehicles with holonomic constraints in environments with obstacles. Our approach uses Pythagorean Hodograph (PH) curves to connect vertices of the tree, which makes it possible to generate paths for which the main kinematic constraints of the vehicle are not violated. These paths are converted into trajectories based on feasible speed profiles of the robot. The smoothness of the acceleration profile of the vehicle is indirectly guaranteed between two vertices of the RRT tree. The proposed algorithm provides fast convergence to the final trajectory. We still utilize the properties of the RRT to avoid collisions with static, environment bound obstacles and dynamic obstacles, such as other vehicles in the multi-vehicle planning scenario. We show results for a set of small unmanned aerial vehicles in environments with different configurations.