**9. Conclusion**

In this work, a vision-based sliding mode control for autonomous landing of a quadrotor UAV is proposed. The vision algorithm is developed to detect the centroid, position and orientation of the camera with respect to a landing pad marker (ArUco marker) placed on the roof of a car. The designed sliding mode controller proves to be effective when working alongside the developed vision algorithm and is simulated using MATLAB environment. This is then on extended to the actual experimental tests on the DJI Matrice M100, in indoor and outdoor environments. The main conclusions are summarized as follows:


All of the results presented above are quiet promising and can be reproduced in any quadrotor system. Reference [20] demonstrates the results of the proposed work. As a future addition to this work, readers can consider using EKF to infuse IMU data with vision to enhance the tracking data. In addition, the users can also improve the proposed SMC to incorporate power rate reaching laws or super twisting laws to attenuate chattering further.

*Vision-Based Autonomous Control Schemes for Quadrotor Unmanned Aerial Vehicle DOI: http://dx.doi.org/10.5772/intechopen.86057*
