<p>A multi-agent system is a system in which multiple agents cooperate to achieve a global objective. Each agent within the system can move independently and exchange information with other agents to collaborate in executing tasks. As an entertainment application of multi-agent systems, previous research has been conducted to realize a mass game in which a group of small robots displays static images. Additionally, with the recent advancements in text-to-image generative models (e.g., stable diffusion), image generative AI has rapidly gained popularity across various fields. In this paper, we propose ChatRAD, a system that integrates image generative AI with a multi-agent system, allowing a group of robots to display animations based on text input from users. We describe the detailed structure and functionality of the system, as well as the control laws governing the robot swarm. Numerical experiments are conducted using multiple target animations to evaluate the system’s performance. Furthermore, to enhance the quality of the displayed animations, we apply Bayesian optimization for gain tuning and verify its effectiveness using image evaluation indices.</p>