Title: Robotics and autonomous systems: metaheuristic optimisation and deep learning

Authors: Le Tuan Anh; Nguyen Van Duc; Trung Van Nguyen; Nguyen Thuy Dung; Nguyen Ho Quang; Pham Van Huy; Than Le

Addresses: Institute of Engineering and Technology, Thu Dau Mot University, Thu Dau Mot City, Vietnam ' Faculty of Engineering, University of Education and Technology, Ho Chi Minh City, Vietnam ' Faculty of Information Technology, Van Lang University, Ho Chi Minh City, Vietnam ' Faculty of Information Technology, University of Economics-Technology for Industries, Ha Noi City, Vietnam ' Institute of Engineering and Technology, Thu Dau Mot University, Thu Dau Mot City, Vietnam ' Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam ' Institute of Engineering and Technology, Thu Dau Mot University, Thu Dau Mot City, Vietnam

Abstract: Autonomous systems and mobile robots are increasingly developed and applied in large-scale areas of life. This paper focuses on navigation for autonomous systems and slamming to create stable systems when exploiting dynamic environments. Firstly, a solution built on simulation annealing, which is an approximation function dealing with global optimum using probability, solves the problem of metaheuristic optimisation. A high-level procedure is used to find the optimal trajectory, which is still the novel challenge of autonomous systems and robotics in unstructured environments. Next, the process of moving in the unknown environment is handled based on the tangent bug algorithm to help avoid collisions and move to the target. In addition, the system also uses deep learning algorithms to identify users through the built-in camera. The developed robot can be an optimal destination trajectory to reduce the cost of the system, moving from the robot position to the required position in an unknown environment, and analysing and recognising the user's face.

Keywords: motion planning; autonomous system; deep learning; local minimum; simulated annealing.

DOI: 10.1504/IJCVR.2025.149829

International Journal of Computational Vision and Robotics, 2025 Vol.15 No.6, pp.756 - 768

Received: 09 Feb 2023
Accepted: 15 Nov 2023
Published online: 14 Nov 2025 *

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