Toward Bezier Curve Bank-Turn Trajectory Generation for Flying Robot

Abstract

This paper presents a UAV maneuver planning with an objective is minimize a total maneuvering time and a load factor when the UAV follows an agile maneuvering path. The Genetic algorithm (GA) combined by fuzzy logic approach will lead this challenging work to meet the best maneuvering trajectories in an UAV operational. It considers UAV operational limits such as a minimum speed, a maximum speed, a maximum acceleration, a maximum roll angle, a maximum turn rate, as well as a maximum roll rate. The feasible maneuvering path will be searched first, and then it will be processed to generate the feasible flight trajectories. There are two ways to follow the maneuvering path: constant speed strategy or changing speed strategy. The first strategy is simple; however it will involve the higher load factor. The changing speed strategy is very engaging technique to reduce the load factor during the maneuver; however it needs to generate the speed as function of time which is feasible to be conducted. The trajectory planner needs to keep the speed inside the UAV flight zone. This paper also proposed the strategy in generating the feasible flight trajectory. To investigate the performance of the proposed strategy the simulation environment has been built by creating a program in MATLAB software. Results show that the load factor can be reduced into lower value which is very engaging to be conducted on going to an autonomous goal of the UAV which has an ability to perform the agile maneuvering. © Springer-Verlag Berlin Heidelberg 2012.