Development and implementation of a method for coordinating the movement of intelligent autonomous mobile robots

Project Manager: Kyzyrkanov A.E.

Funding source: GF of young scientists for the project “Zhas Galym”

Project objective: development of an algorithm for controlling the movements of simple autonomous self-organizing mobile robots in a swarm so that the swarm can move in a coordinated manner, without colliding with each other or obstacles, choosing the most optimal trajectory to reach the goal.

Years of implementation: 2024 – 2026

Amount of funding: 29,976,690 tenge

1. Comprehensive Literature Review: Collect and analyze existing research and publications on robot swarm control algorithms, with a focus on the work of international experts, to establish a foundation for understanding and identifying innovative practices in this field.
2. Algorithm Development for Ground Robot Swarms:

• Innovative Design: Develop a sophisticated control and coordination algorithm specifically for a swarm of ground wheeled robots, focusing on collective behavior and efficient execution of various tasks.
• Simulation-based Implementation: Implement and debug this algorithm in a simulated environment designed for ground wheeled robots, ensuring an accurate reproduction of real-world conditions.

3. Experimental Testing and Optimization:

• Rigorous Evaluation: Conduct comprehensive experimental studies to test and evaluate the developed algorithm in various simulated scenarios, evaluating its performance in different tasks and environments.
• Troubleshooting: Systematically identify and correct any issues, bugs, or inefficiencies found during testing to improve the robustness and efficiency of the algorithm.

4. Algorithm Refinement for Multi-Environment Applications:

• Adaptation for 3D Environments: Refine and adapt the developed algorithm for use in aerial and underwater robotic systems, ensuring efficient functionality and navigation in 3D spaces.
• Versatility across Environments: Achieve an algorithm design that will seamlessly integrate with the unique hardware and software requirements of both aerial and underwater robots.

5. Rigorous Testing in Simulated Environments:

• Extensive Testing in 3D Spaces: Thoroughly test the adapted algorithm in simulated aerial and underwater environments, evaluating its adaptability, efficiency, and robustness in various 3D scenarios.
• Continuous Improvement: Focus on identifying and resolving any operational issues or technical errors in these diverse environments.