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The paper reviews the goal of controlling mobile robot movement along the planned path. It proposes an adaptive robot movement control algorithm, allowing to increase the precision of holding the robot within the prescribed path under the conditions of unstable navigation field. The adaptation of the algorithm to jamming environment is in redistributing weights of the weighted sum of estimates given by the ultrasound navigation system (USNS) and wheel pulse transducers (WPT). When precision of the USNS reduces affect of the WPT on the final estimate increases while affect of the USNS decreases. Such a redistribution is carried out when the system is operating due to changing elements of a measurement noise matrix in Kalman filter [1] with use of which a mobile robot heading angle is estimated. Corresponding elements of the measurement noise matrix increase along with increase of deviation of the mobile robot trajectory from a straight line. The extent of deviation calculated as the standard error of a regression is defined by means of the statistical analyses involving the last n measurements contained in buffer store of the USNS. The obtained results demonstrate significant benefit of the developed mobile robot heading estimation algorithm in comparison with the conventional filtering algorithm basing on using the classical Kalman filter with the measurement noise matrix whose elements are fixed.

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Algorithms for the organization of standalone operation of a robotic manipulator have been considered in this Article. The controls on the control panel of a man-made equipment piece have been the manipulated object. A robotic manipulator fitted with a control system, and a machine vision system, have been the subsystems under study. The robotic manipulator interacts with the objects to switch on and off a toggle switch, turn a rotary switch, press on a pushbutton, etc. Manipulating the objects in question involves assessing of their positions and orientations, which is achieved through the machine vision system. Coordinated operation of the subsystems is required to plan and to implement control of the manipulator, while taking into account positions of the objects relative to each other. A configuration of interactions between the manipulator and the control panel, a method for organizing coordinated functioning of the machine vision system when manipulating controls, which includes assessing positions of the object of interest relative to the robotic manipulator, and an algorithm for planning control based on artificial neural network technology have been presented in this Article.