Introducing M: A Modular, Modifiable Social Robot

2026-03-19

AI Summary

This work addresses the challenges of reproducibility, limited adaptability, and deployment complexity commonly encountered in social robotics research by introducing M—a low-cost, open-source, and highly modular social robot platform. M integrates a modular mechanical design, multimodal perception capabilities, a streamlined expressive behavior-driven architecture, and a native ROS 2 software stack, enabling clear decoupling among perception, expression, and data management. The platform also provides a consistent simulation environment that facilitates efficient sim-to-real transfer. Through participatory design and a week-long in-home field deployment, the study demonstrates M’s practicality, scalability, and robustness in real-world settings, showcasing its effectiveness in representative interaction paradigms such as storytelling and conversational tutoring.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Machine Learning: Multimodal Learning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

We present M, an open-source, low-cost social robot platform designed to reduce platform friction that slows social robotics research by making robots easier to reproduce, modify, and deploy in real-world settings. M combines a modular mechanical design, multimodal sensing, and expressive yet mechanically simple actuation architecture with a ROS2-native software package that cleanly separates perception, expression control, and data management. The platform includes a simulation environment with interface equivalence to hardware to support rapid sim-to-real transfer of interaction behaviors. We demonstrate extensibility through additional sensing/actuation modules and provide example interaction templates for storytelling and two-way conversational coaching. Finally, we report real-world use in participatory design and week-long in-home deployments, showing how M can serve as a practical foundation for longitudinal, reproducible social robotics research.

Problem

• social robotics
• platform friction
• reproducibility
• real-world deployment
• modular design

Innovation

• modular robot
• open-source platform
• sim-to-real transfer
• ROS2-native
• social robotics