BIO-INSPIRED PRINCIPLES FOR MODELING INFORMATION COLLECTION IN COLLABORATIVE ROBOT ENVIRONMENTS

The article considers bioinspired principles as a basis for developing models of information collection in the environment of collaborative robots. Special attention is paid to the study of the collective behavior of biological systems, such as anthills, flocks of birds and swarms of bees, which serve as a source of inspiration for building decentralized algorithms. The application of the Ant Behavior Optimization (ACO) method is proposed to implement flexible and adaptive strategies for exploring environments with obstacles. The obtained modeling results demonstrate the effectiveness of the algorithm under conditions of partial uncertainty, agent autonomy and limited sensory information. The potential for further development of bioinspired models in the field of robotic systems for autonomous exploration of complex environments is highlighted.