Alexey Matveev

This paper deals with the problem of autonomously driving a mobile robot to the source of an unknown planar scalar environmental field based on pointwise measurement of its value at the current location of the robot. An underactuated nonholonomic Dubins car-like robot with a bounded control range is handled. A novel bioinspired algorithm based on hybrid control paradigm is proposed and justified via mathematically rigorous results on nonlocal convergence. This algorithm assumes the use of only two field sensors and does not require measuring or estimating the field gradient. It is also shown that, in the case of an extended source represented by a curve, the proposed algorithm endows the robot with the ability to track this curve, thereby exhibiting its layout. Theoretical results are confirmed with computer simulation experiments. The proposed control law is efficient both computationally and in terms of the resulting motion.

The paper handles the problem of automatic path tracking by an autonomous off-road eightwheeled robotic vehicle subject to uncertain longitudinal and lateral wheel slips. A sliding mode guidance law is proposed that solves this problem, explicitly takes into account the constraints on the control inputs, and ensures tracking of any path whose contortion lies within given bounds. Necessary conditions for the mission feasibility are first established. Under slight and partly inevitable enhancement of them, nonlocal convergence and robust stability of the proposed guidance law are theoretically justified. In doing so, the slipping effects are treated as bounded uncertainties. Simulation results confirm the applicability and performance of the control law.