scholarly journals Artificial Intelligence Control in 4D Cylindrical Space for Industrial Robotic Applications

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 174833-174844
Author(s):  
Andrea de Giorgio ◽  
Lihui Wang
Keyword(s):  
Artificial Intelligence ◽  
Intelligence Control ◽  
Robotic Applications

Predictability of AI Decisions

2021 ◽  
pp. 17-28
Author(s):  
Grzegorz Musiolik
Keyword(s):  
Artificial Intelligence ◽  
Reinforcement Learning ◽  
Free Will ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Mathematical Structure ◽  
General Question ◽  
Safety Issues ◽  
Robotic Applications ◽  
Mathematics And Physics

Artificial intelligence evolves rapidly and will have a great impact on the society in the future. One important question which still cannot be addressed with satisfaction is whether the decision of an intelligent agent can be predicted. As a consequence of this, the general question arises if such agents can be controllable and future robotic applications can be safe. This chapter shows that unpredictable systems are very common in mathematics and physics although the underlying mathematical structure can be very simple. It also shows that such unpredictability can also emerge for intelligent agents in reinforcement learning, especially for complex tasks with various input parameters. An observer would not be capable to distinguish this unpredictability from a free will of the agent. This raises ethical questions and safety issues which are briefly presented.

Internet of Things and Robotic Applications in the Industrial Automation Process

2021 ◽  
pp. 50-64
Author(s):  
Seeja G. ◽  
Obulakonda Reddy R. ◽  
Korupalli V. Rajesh Kumar ◽  
S. S. L. C. H. Mounika ◽  
Reddy Madhavi K.
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Production Cost ◽  
Industrial Development ◽  
Industrial Applications ◽  
Vital Role ◽  
Industrial Automation ◽  
Industrial Operations ◽  
Industrial Productivity ◽  
Robotic Applications

The recent industrial scenarios project its advancements and developments with the intervention of integrated technologies including internet of things (IoT), robotics, and artificial intelligence (AI) technologies. Industrial 4.0 revolutions have broken the barriers of all restricted industrial boundaries with the act of those interdisciplinary concepts and have taken a keen part in industrial development. Incorporation of these advancements considerably helps in improving product efficiency and in reducing the production cost. Based on categories of production, industrial automation processes may vary. In this regard, robots are playing a vital role to automate the production process at various levels of industrial operations. The combination of IoT, robotics, and AI technologies enhances the industrial productivity towards getting the success rate. This chapter focuses on how robotic technology with IoT and AI methods enhances the limitations of various industrial applications.

scholarly journals Robotariums implementations witn the Elements of Artificial Intelligence Control

2020 ◽  
pp. 0973-0985
Author(s):  
Alexander Aryskin ◽  
Oleg Davydov ◽  
Stanislav Eprikov ◽  
Alexander Ksenzenko ◽  
Valentin Pryanichnikov ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligence Control

scholarly journals Prototype Cross Platform Oriented on Cybersecurity, Virtual Connectivity, Big Data and Artificial Intelligence Control

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 197939-197954
Author(s):  
Alessandro Massaro ◽  
Michele Gargaro ◽  
Giovanni Dipierro ◽  
Angelo Maurizio Galiano ◽  
Simone Buonopane
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Cross Platform ◽  
Intelligence Control

Artificial Intelligence Control Algorithm for the Steering Motion of Wheeled Soccer Robot

2019 ◽  
Vol 33 (10) ◽  
pp. 1959034 ◽  
Author(s):  
Xiaowei Xiong
Keyword(s):  
Artificial Intelligence ◽  
Control Algorithm ◽  
Steering Wheel ◽  
Dynamic Feedback ◽  
Steering Control ◽  
Soccer Robot ◽  
Artificial Neurons ◽  
Intelligence Control ◽  
Intelligent Model ◽  
Soccer Robots

In this paper, the artificial intelligence control algorithm for steering robot of steering wheel is studied. The steering movement of wheeled soccer robot is controlled by artificial intelligence control algorithm, and the steering movement is modeled and simulated. Firstly, the characteristics of artificial neurons are simulated and a similar control model is constructed to complete the simulation of football. The artificial intelligence control algorithm has a dynamic feedback item compared with the traditional intelligent model, which has a better effect on the steering control of the wheeled soccer robot. In this paper, artificial intelligence control algorithm is used to optimize the parameters of artificial intelligence control algorithm, and the output of control signal of each steering part of wheeled soccer robot is simulated in the experiment, and the control of the steering action of wheeled soccer robot by artificial intelligence control algorithm is verified by experiments. Then the artificial intelligence control algorithm forms the connection structure. This method provides a good reference for steering control of wheeled soccer robots.

A Simulation Research of Artificial Intelligence Control

2012 ◽  
Vol 214 ◽  
pp. 640-643
Author(s):  
Xin Xiong ◽  
Chao Dong Lu
Keyword(s):  
Artificial Intelligence ◽  
Control System ◽  
Control Method ◽  
Control Mode ◽  
Simulation Research ◽  
Loop Control ◽  
Complex Control ◽  
Intelligence Control ◽  
And Control ◽  
Specific Control

The traditional control system can not meet the more complex control tasks of the problem, using artificial intelligence control method of imitation, artificial intelligence control system on the overall structure of the design, and given the specific control algorithms. System relies on accurately identify the various features of the error and make the appropriate decisions to multiplexing, open, closed loop control mode of combining control and solve the complex control of the process of identification, decision-making and control problems and achieve A unified identification control.

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