The advantages of anthropomorphic robotics include the ability to work in a human-oriented environment and the performance of complex tasks that usually only a person can cope with. One of the most important tasks in this area is the development of powerful anthropomorphic grippers. For several reasons anthropomorphic grippers with group drives are promising, in which movement from several joints is performed from one drive. The purpose of the article is a kinematic analysis of one of the possible design of such a gripper. In the article solved the direct and inverse problems of kinematics in an analytical form using the geometric method. The dependences of the Cartesian coordinates of the joints of the fingers on the joint coordinate describing the motion of a group drive were obtained for the solving the direct kinematic problem. The dependences between the joint coordinate of a group drive and desired position of the finger joints or the orientation of its links were obtained for solving the inverse problem of kinematics. The obtained results can be used further for performing dynamic analysis, parametric synthesis of the design and synthesis a control system for an anthropomorphic gripper with group drive.
Decentralized multi-agent robotic systems have many advantages over centralized ones. Such systems make it possible to distribute computational and communication operations between all its elements, and are also more resistant to the loss of individual elements of a swarm, but they complicate the implementation of complex high-level tasks. An example of such a problem is the selection of one of the possible alternatives, in which the swarm must choose the most favorable solution from a list of possible alternatives. This paper proposes an algorithm for reaching a consensus for robotic swarms deployed in scenarios in which they can choose one of the two most common signs in the external environment. The proposed algorithm is based on the calculation of the measured features of the environment, as well as the distribution of this data between robots. The algorithm was tested using the ARGoS simulator.
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.
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