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2 Annals of Computer Science and Information Systems

2 2021

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Mobile robots interacting with obstacles control based on artificial intelligence

Chuyen Tran Duc, Hoa Roan Van, Dien Nguyen Duc, Nguyen Tung Lam

Annals of Computer Science and Information Systems

2021

Vol. 27

13--16

In this paper, research on the applications of artificial intelligence in implementing Deep Deterministic Policy Gradient (DDPG) on Gazebo model and the reality of mobile robot has been studied and applied. The goal of the experimental studies is to navigate the mobile robot to learn the best possible action to move in real-world environments when facing fixed and mobile obstacles. When the robot moves in an environment with obstacles, the robot will automatically control to avoid these obstacles. Then, the more time that can be maintained within a specific limit, the more rewards are accumulated and therefore better results will be achieved. The authors performed various tests with many transform parameters and proved that the DDPG algorithm is more efficient than algorithms like Q-learning, Machine learning, deep Q-network, etc. Then execute SLAM to recognize the robot positions, and virtual maps are precisely built and displayed in Rviz. The research results will be the basis for the design and construction of control algorithms for mobile robots and industrial robots applied in programming techniques and industrial factory automation control.

Control design of an UAV–Q based on feedback linearization and optimum modulus methods

Chuyen Tran Duc, Huy Hoang Van, Nguyen Tung Lam

Annals of Computer Science and Information Systems

2021

Vol. 27

17--22

In the paper, we present the formulation of quadrotor control loops that are based on a decomposition into a cascade structure and the use of feedback linearization and optimum modulus methods to determine controller parameters. The dynamic model used in this paper considers the dynamics of the propeller rotor drive systems. The propeller rotor drive systems are considered as a linear actuated system. After the synthesizing of the controllers is completed, the system is simulated in MATLAB/Simulink. The results from this work can be useful for the development of autonomous algorithms for UAV-Q (Unmanned Aerial Vehicle Quadrotor). The research results serve as the basis for control algorithms development for other similar systems.