Opinion-Driven Decision-Making for Multi-Robot Navigation through Narrow Corridors

-- We propose an opinion-driven navigation framework for multi-robot traversal through a narrow corridor . Our approach leverages a multi-agent decision-making model known as the Nonlinear Opinion Dynamics (NOD) to address the narrow corridor passage problem, formulated as a multi-robot navigation game. By integrating the NOD model with a multi-robot path planning algorithm, we demonstrate that the framework effectively reduces the likelihood of deadlocks during corridor traversal. T o ensure scalability with an increasing number of robots, we introduce a game reduction technique that enables efficient coordination in larger groups. Extensive simulation studies are conducted to validate the effectiveness of the proposed approach. In recent years, robots have become increasingly integrated into human environments, including residential areas, healthcare facilities, and public spaces. As robots interact frequently with both humans and other robots, the importance of social navigation has grown significantly. Social navigation focuses on optimizing a robot's behavior to enhance human comfort and improve the acceptability of robots in shared spaces. For instance, when multiple robots navigate through a narrow corridor, as depicted in Figure 1, they must dynamically adapt their movements in response to the actions of others, ensuring smooth and cooperative interactions within such constrained environments.