Predictive Assessment of Operator's Hand Trajectory with the Copying Type of Control for Solution of the Inverse Dynamic Problem

The most important task of modern robotics is the development of robots to perform the work in potentially dangerous fields which can cause the risk to human health. Currently robotic systems can not become a full replacement for man for solving complex problems in a dynamic environment despite an active development of artificial intelligence technologies. The robots that implement the copying type of control or the so-called virtual presence of the operator are the most advanced for use in the nearest future. The principle of copying control is based on the motion capture of the remote operator and the formation of control signals for the robot’s drives. A tracking system or systems based on movement planning can be used to control the drives. The tracking systems are simpler, but systems based on motion planning allow to achieve more smooth motion and less wear on the parts of the control object. An artificial delay between the movements of the operator and the control object for necessary data collection is used to implement the control-based motion planning. The aim of research is a reduction of delay, which appears when controlling the anthropomorphic manipulator drives based on the solution of the inverse dynamic problem, when real time copying type of control is used . For motion path planning it is proposed to use forecast values of the generalized coordinates for manipulator. Based on the measured values of the generalized coordinates of the operator's hand, time series are formed and their prediction is performed. Predictive values of generalized coordinates are used in planning the anthropomorphic manipulator trajectory and solving the inverse dynamic problem. Prediction is based on linear regression with relatively low computational complexity, which is an important criterion for the system operation in the real time operation mode. The developed mathematical apparatus, based on prediction parameters and maximum permissible accelerations of the manipulator drives, allows to find a theoretical estimate of error values limits for planning the operator's hand trajectory using the proposed approach for specific tasks. The adequacy of the maximum theoretical value of the prediction error, as well as the prospects of the proposed approach for testing in practice is confirmed by the software simulation in Matlab environment.