Sliding Mode Controller navigation algorithm using tag-based fiducial marker detection and fuzzy logic system

Autonomous navigation of vehicles, especially drones, plays an essential role in Industrial Revolution 4.0. Maneuvering drone in complex path especially indoor environment requires stable and accurate navigation system. This paper investigates a navigation algorithm for maneuvering a drone by Sliding Mode Controller (SMC) combined by fuzzy logic system, model reference approach, and tag-based fiducial marker detection in an indoor environment. The SMC parameters are tuned by the fuzzy logic system and model reference approach. A drone model is simulated in a virtual indoor environment to validate the performance of the navigation system with different home points and trajectories. The desired set-points of the control system are obtained by AprilTag, which is a tag-based fiducial marker detection system. The stability of the SMC was verified using the Lyapunov stability theory. The performance of proposed SMC navigation algorithm validated by comparing to conventional controllers which represents the effectiveness of SMC. It can be ascertained that the proposed SMC navigation algorithm is applicable to maneuver the drone for various industrial tasks in indoor environment.