A Nonlinear Camera Gimbal Visual Servoing Control using Command Filtered Backstepping

Abstract

This paper presents a method for modeling both the motion of a target feature in a camera sensor plane of images and the movement of a pan-tilt gimbal mechanism that is usually mounted on a fixed-wing unmanned aerial vehicle (UAV). The target features can be obtained from a common method of a feature extraction. Here, we utilize an image extraction method of Tracking, Learning, and Detection (TLD) that have a prominent long-term tracking. Futhermore, we employ an image base visual servoing (IBVS) control method to direct the camera always pointing at an object target in a distance using the pan-tilt gimbal mechanism while the fixed-wing UAV cruising above. Our works are modeling a nonlinear camera gimbal movement and designing a nonlinear adaptive control of command filtered backstepping (CFBS) to make a solution for the nonlinear IBVS control problem that have complicated movements of the image features and the gimbal pan-tilt mechanism in despite of the radical movements of the UAV itself. We also show that the CFBS design is easier than integral backstepping (IBS) because no requirement of model derivation procedure. Software and hardware in the loop simulation (SILS / HILS) results show the stability of the control of IBVS using CFBS.