Multimodal Communication in Human&Robot Interaction  offers a comprehensive, systems-level framework for designing robots that communicate in natural, human-like ways. As robots move into homes, hospitals, factories, classrooms, and public spaces, effective interaction can no longer rely on single-modality interfaces. Instead, robust communication demands the seamless integration of speech, gesture, vision, motion, probabilistic reasoning, cooperative control, and explainable artificial intelligence. This book unifies speech processing, computer vision, object and gesture recognition, audiovisual synchronization, probabilistic robotics, motion planning, collaborative control, and generative conversational AI within a coherent perception&action architecture. Rather than presenting these technologies as isolated components, it demonstrates how they operate together to interpret human intent, act safely and predictably, and communicate reasoning transparently. A central contribution is its emphasis on robots that not only understand multimodal human signals but also generate aligned speech, gesture, motion, and explanation in context-sensitive and safety-aware ways. Ethics is treated as a foundational design dimension. The book addresses bias, explainability, accountability, transparency, and the environmental impact of AI systems, while also engaging deeper questions surrounding consciousness, sapience, and superintelligence. It bridges computational modeling with communication theory and ethical frameworks, integrating data-driven learning with principles of trust and human dignity. Structured in eight interconnected parts with consistent pedagogical features-conceptual foundations, technical development, examples, readings, and exercises-this volume supports advanced coursework, research, and real-world system design. It provides the technical and ethical foundations needed to build intelligent, trustworthy, and socially responsible multimodal robotic systems.