A cooperating intelligent control system based on expert systems and neural networks

1994 ◽  
Author(s):  
Tingkai Wang
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Expert Systems ◽  
Intelligent Control ◽  
Intelligent Control System

scholarly journals THE INTELLIGENT ROBOT MITSUBISHI RV-2JA CONTROL SYSTEM

2020 ◽  
Author(s):  
V.F. Bonilla ◽  
◽  
A.V. Litvin ◽  
M.H. Moya ◽  
G.K Moskera ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Control System ◽  
Intelligent Control ◽  
Robot Control ◽  
Intelligent Robot ◽  
Intelligent Control System ◽  
And Control ◽  
Electromyographic Signals ◽  
Semg Signals

The Mitsubishi RV-2JA intelligent robot control system (ISMS) was synthesized using surface electromyographic signals (pEMG). The sEMG signals were recording using the Myo bracelet and transmitted to the intelligent control system via the Bluetooth interface. The IRCS was synthesized in Simulink environment of the Matlab platform. IRCS performs the processing and analysis of sEMIG signals to identify, verify and control the robot using an artificial neural networks.

scholarly journals Intelligent Technologies and Robotic Machines for Garden Crops Cultivation

2021 ◽  
Vol 15 (4) ◽  
pp. 35-41
Author(s):  
I. G. Smirnov ◽  
D. O. Khort ◽  
A. I. Kutyrev
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Intelligent Control ◽  
Industrial Robots ◽  
Fixation Time ◽  
Software Environment ◽  
Technical Standards ◽  
Real Time Processing ◽  
Software Complex ◽  
Intelligent Control System

The existing models of industrial robots cannot perform technological processes of apple harvesting. It is noted that there is a need for developing special actuators, grippers and new control algorithms for harvesting horticulture products. (Research purpose) The research aimed to develop an intelligent control system for horticulture industrial technologies and robotic techniques for yield monitoring and fruit harvesting. (Materials and methods) The research methodology was based on such modern methods as computer modeling and programming. In particular, the following methods were applied: systems analysis, artificial neural networks theory, pattern recognition, digital signal processing. The development of software, hardware and software was carried out in accordance with the requirements of GOST technical standards. The following programming languages were used: (C / C ++)-based  OpenCV library, Spyder Python Development Environment, PyTorch and Flask frameworks, and JavaScript. Image marking for training neural networks was carried out via VGG ImageAnnotator and in Labelbox. The design process was based on the finite element method, CAD SolidWorks software environment. (Results and discussion) An intelligent management system for horticulture industrial technologies has been created based the on the «Agrointellect VIM» hardware and software complex. The concept of the system is shown to be implemented via computer and communication technology, robotic machines, the software for collecting, organizing, analyzing and storing data. The gripper proves to fix an apple gently and holds it securely. Depending on the size, the fruit fixation time is 1.5-2.0 seconds, the fruit maximum size is 85 per 80 millimeters , and its maximum weight is 500 grams. (Conclusions) The developed intelligent control system for industrial technologies based on «Agrointellect VIM» hardware and software complex ensures the efficient real-time processing of information necessary for the design of intelligent agricultural technologies using robotic machines and artificial intelligence systems.

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