Improved tangent bug algorithm with log-barrier lyapunov function for obstacle avoidance in four-wheeled mobile-robots

In this paper, an improved tangent bug (I-TB) algorithm specifically designed for obstacle avoidance of a four-wheeled mobile-robot is presented. The I-TB algorithm utilizes point cloud data to detect obstacles and provides a desired reference for obstacle avoidance. This algorithm is integrated with a log-barrier Lyapunov function (BLF) based backstepping controller to develop a kinematic guidance law. The log-BLF based backstepping controller ensures that the tracking error remains within predefined boundaries, even in the presence of external disturbances. The stability analysis of the proposed controller guarantees the uniform ultimate boundedness of the guidance algorithm. The complete dynamics of the four-wheeled mobile-robot are modelled and verified using the bond-graph (BG) approach. Further, the effectiveness of the proposed I-TB algorithm combined with the log-barrier Lyapunov function is validated through both simulations and experiments on a custom-built mobile-robot equipped with a laser rangefinder (LRF) sensor.