Adaptive vision-based control of an unmanned aerial vehicle without linear velocity measurements. (November 2016) - Jabbari Asl, Hamed; Yoon, Jungwon
Abstract: In this paper, an image-based visual servo controller is designed for an unmanned aerial vehicle. The main objective is to use flow of image features as the velocity cue to compensate for the low quality of linear velocity information obtained from accelerometers. Nonlinear observers are designed to estimate this flow. The proposed controller is bounded, which can help to keep the target points in the field of view of the camera. The main advantages over the previous full dynamic observer-based methods are that, the controller is robust with respect to unknown image depth, and also no yaw information is required. The complete stability analysis is presented and asymptotic convergence of the error signals is guaranteed. Simulation results show the effectiveness of the proposed approach. Abstract : Highlights: A new vision-based controller is proposed for the underactuated quadrotor UAV. The controller accounts for low quality of linear velocity information obtained from accelerometers. An adaptive scheme is proposed to compensate for the unknown depth information of the image. The controller does not require the yaw information of the UAV. The approach considers the full dynamics of the quadrotor.