A real-time angle deviation detection and measurement technique for straight line quadrocopter navigation using accelorometer

Deviation from a planned path due to dynamic wind disturbances clearly will defect the quadrocopter navigation accuracy thus result to poor execution of a task. Few researchers proposed correction algorithms to be integrated in the autonomous quadrocopter system for the problem arises. However, the algorithms are not applicable to enable quadrocopter to navigate precisely on a planned trajectory around the small area with presences of dynamic disturbances such as wind. The research proposed a preliminary work for new real-time adaptive trajectory correction algorithm for autonomous quadrocopter, specifically the algorithm for angle deviation detection and measurement technique via an accelerometer. A ±3G analog accelerometer is utilized and being interfaced with a low-cost microcontroller for digitization process. For minimizing the fluctuation of accelerometer discrete signals, a simplified Kalman's filter algorithm appropriated for the controller is employed. The filtered signals are then used to sense the quadrocopter deviation from the planned path and compute the angle. A custom-made X-Y platform is used as the straight navigation path and represented as dynamic control environment. A GUI window is built in order to exhibit the visual deviation experienced by quadrocopter and recorded wirelessly the deviation angle from the controller so that evaluation on the accuracy performance can be analyzed. Three experiments with a different range of wind disturbance acceleration are executed where the results reveal that the technique is applicable to be used for short-duration detection and in a small-bounded area with fine accuracy.