The Role of Collective Intelligence in Optimizing the Performance of Multiple Robots

Multi-robotic systems with the ability to perform complex tasks in a coordinated manner play an important role in applications such as warehouse management, search and rescue, and smart agriculture. These systems face challenges such as task allocation, optimal routing, and reducing energy consumption in dynamic environments. In this research, collective intelligence algorithms including ant colony optimization, particle swarm optimization, and firefly algorithm are used to address these challenges. The above algorithms, inspired by natural behaviors, enable improved coordination and increased efficiency in multi-robotic systems. Simulation results in dynamic environments showed that the combination of these algorithms improves the scalability, flexibility, and stability of multi-robotic systems in changing conditions.

کلیدواژه ها:

Collective intelligence ، collective robots ، multi-robotics