Advanced Path Planning and Collision Avoidance Algorithms for UAVs
Design and application of Kinematic A and Nonlinear Model Predictive Control to autonomous flight
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The book aims to present innovative algorithms to provide autonomous flight capability to a fixed-wing unmanned aircraft. Particularly it contributes to research on path optimization, trajectory tracking and collision avoidance with two algorithms designed respectively for path planning and aircraft guidance. These algorithms are combined to generate the shortest path from start to target avoiding known obstacles represented on a map and to drive the aircraft on the optimum path avoiding unpredicted objects sensed in flight. The path planning algorithm, named Kinematic A , is developed on the ...
The book aims to present innovative algorithms to provide autonomous flight capability to a fixed-wing unmanned aircraft. Particularly it contributes to research on path optimization, trajectory tracking and collision avoidance with two algorithms designed respectively for path planning and aircraft guidance. These algorithms are combined to generate the shortest path from start to target avoiding known obstacles represented on a map and to drive the aircraft on the optimum path avoiding unpredicted objects sensed in flight. The path planning algorithm, named Kinematic A , is developed on the basis of graph search algorithms like A or Theta and is meant to generate feasible paths through a simple aircraft kinematic-model, evaluating moving cost between nodes of tridimensional graphs. The guidance algorithm on the other hand faces the concurring tasks of trajectory tracking and collision avoidance with Nonlinear Model Predictive Control. It exploits the optimal path provided with KA and a visual servoing control logics based on a spherical camera to steer the aircraft toward the desired path.
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