Robust Vision-Based Sliding Mode Control for Uncooperative Ground Target Searching and Tracking by Quadrotor

In this paper, the problem of searching and tracking uncooperative and unidentified mobile ground target using a quadcopter unmanned aerial vehicle (QUAV) is investigated. The proposed strategy is an Image-Based Visual Servoing (IBVS) approach, combined with the virtual camera concept and robust control. This strategy makes use of the rough prior information of the target, in contrast with existing strategies, which will alleviate the problem of altitude estimation noise and enhance the overall accuracy. Hence, a new vision-based sliding mode controller (SMC) is designed to control the quadcopter taking into account the flight phase's heterogeneity, the external disturbances and parameters uncertainties as well as the target maneuverability. In order to get a better insight about the SMC tuning and adjustment, three different reaching laws are evaluated and compared. The proposed controller allows an automatic execution of the flight strategy whilst the searching phase relies on the Camera Coverage Area (CCA) technique. The vision-based technique allows an automatic QUAV altitude tuning for optimal target observation and tracking. Another contribution of this work is the fact that the designed controller validity and stability overspan the entire scenario to reach the universal and to smoothen out surges generated by control switching. Numerical simulations are conducted to compare the proposed SMC controllers and validate the effectiveness of the whole strategy.