Micro air vehicle path planning in fuzzy quadtree framework

Fuzzy quadtree framework has been utilized to develop a path planner for a fixed wing micro air vehicle (MAV). The fuzzy quadtree being computationally efficient can efficiently meet the computational requirements of a micro air vehicle, and therefore, does not require high capacity processor onboard. The proposed algorithm can provide optimal and safe path because it can avoid a pop up obstacle in real time while significantly reducing both the space and the time complexity. Some issues which are very pertinent to the MAV path planning like vehicle dimensions and safety measures for congested environment have been taken into account in the code developed. Besides, during the quadtree generation the constraint of turn rate kinematics of the MAV has been included.