Action recognition algorithm from visual sensor data for contactless robot control systems

V. Voronin; M. Zhdanova; I. Khamidullin; E. Semenishchev; A. Zelensky; Yu. Ilyukhin

doi:10.1117/12.2642003

28 October 2022 Action recognition algorithm from visual sensor data for contactless robot control systems

V. Voronin, M. Zhdanova, I. Khamidullin, E. Semenishchev, A. Zelensky, Yu. Ilyukhin

Proceedings Volume 12276, Artificial Intelligence and Machine Learning in Defense Applications IV; 1227604 (2022) https://doi.org/10.1117/12.2642003
Event: SPIE Security + Defence, 2022, Berlin, Germany

Abstract

Automation of production processes using robots is a priority for the development of many industrial enterprises. Robotization is aimed at freeing a person from dangerous or routine work. At the same time, robots are able to perform tasks more efficiently than human, and the collaboration of a human and a robot allows to combine the strengths and effectiveness of robots and human cognitive ability into a single flexible system, and as a result, organize flexible methods of automation and reconfiguration of production processes. In this work, we focused on the implementation of the method of interaction between a person and a robot based on the recognition of gesture commands of a human-operator. An approach based on extraction a human skeleton and classification using a neural network is proposed as a method for recognizing actions. To test the effectiveness of the proposed algorithm, the possibility of transmitting gesture commands to the robot and organizing a contactless control method of the robot, simulation modeling was carried out in the RoboGuid environment. This environment is for industrial robots, provided by Fanuc.

Conference Presentation

Citation Download Citation

V. Voronin, M. Zhdanova, I. Khamidullin, E. Semenishchev, A. Zelensky, and Yu. Ilyukhin "Action recognition algorithm from visual sensor data for contactless robot control systems", Proc. SPIE 12276, Artificial Intelligence and Machine Learning in Defense Applications IV, 1227604 (28 October 2022); https://doi.org/10.1117/12.2642003

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