An Architectural Approach for Multimodal Robot Control

Modern robotic systems increasingly require the integration of heterogeneous interaction modalities and adaptive decision-making capabilities. However, many existing approaches remain loosely coupled and lack a unified architectural perspective. This paper presents an architectural approach for multimodal robot control grounded in distributed collective intelligence. The architecture is organized as a set of interacting autonomous components whose coordination enables the emergence of coherent robot behavior. By framing multimodal interaction and control as a collective process supporting distributed decision-making across modalities, the approach aligns with principles of self-adaptive systems and task-specific collective intelligence. We present the architectural design, its methodological foundations, and its implications for distributed intelligent systems.