Dialogue Control of Collaborative Robots Based on Artifi cial Neural Networks
https://doi.org/10.17587/mau.22.567-576
Abstract
Collaborative robotics progress is based on the possibility to apply robots to the wide range activity of peoples. Now the user can control the robot without any special knowledge in robotics and safe. The price of such possibilities is complication of control system of robot which now has to aquire an opportunity of autonomous behavior under human’s control, using the necessary sensors and elements of artificial intelligence. In our research we suppose the collaborative robot as mobile robotic device possible to fulfil some work under the human’s speech demands not only in the same space with the human. We also suppose the necessity of bilateral dialogue human-robot to make it clear the task, the current situation, the state as robot as human. The complex task of control, or may be the collaboration of human with his artificial partner need new means of control, situation recognition, speech dialogue management. As a mean to solve the whole complex of problems we propose the combination of different artificial neural networks. Such as convolution networks for image recognition, deep networks for speech recognition, LSTM networks for autonomous movement of robot control in current situation. Investigations in the field of mobile and manipulation robots including the human-robot control have been proceeded for some years in the department "Robotic systems and mechatronics" BMSTU celebrating now it 70th years Jubilee. The reader may find some of the works in the bibliography. In result of all these investigations we obtain the service robot model which may find a wide application.
About the Authors
A. S. YuschenkoRussian Federation
Dr. Science Tech., Professor
Moscow, 105005, Russian Federation
Yin Shuai
Russian Federation
Moscow, 105005, Russian Federation
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Review
For citations:
Yuschenko A.S., Shuai Y. Dialogue Control of Collaborative Robots Based on Artifi cial Neural Networks. Mekhatronika, Avtomatizatsiya, Upravlenie. 2021;22(11):567-576. (In Russ.) https://doi.org/10.17587/mau.22.567-576