Invent, Build, Deploy: Creating a Cross-Campus Robotics Ecosystem for the Next Generation of Research and Learning

How can universities expand research capacity for robotics, AI, and autonomous systems while strategically sharing resources and infrastructure across multiple campuses? This session presents a four-year case study of three George Mason University projects that together create a research continuum from invention and experimentation to application and industry engagement.

The Mason Autonomy and Robotics Center (MARC) transforms existing academic space into a robotics research hub anchored by a two-story robotic aviary. At the Life Sciences and Engineering Building (LSEB), a new robotics laboratory supports hands-on teaching, experimentation, and interdisciplinary exploration within a multidisciplinary science and engineering facility. Fuse at Mason Square incorporates a robotics laboratory that extends these capabilities into an urban innovation hub designed to connect university research with industry collaboration and technology development.

Presenters will examine how lessons across the three projects shaped subsequent planning decisions, from renovation versus new construction to determining which robotics capabilities and infrastructure should be specialized, shared, duplicated, or adaptable. The session will explore how emerging requirements were translated into infrastructure and safety strategies while balancing researcher needs, operational constraints, and long-term flexibility. Attendees will gain practical planning tools and lessons learned for evaluating capacity, infrastructure, redundancy, safety, and growth when developing robotics environments across multiple campuses.

Learning objectives:

1. Evaluate renovation versus new construction strategies for robotics research environments based on program needs, existing conditions, infrastructure capacity, adaptability, and opportunities for future growth.
2. Identify infrastructure, spatial, and safety considerations for integrating robotics, AI, and autonomous systems into academic research and teaching environments while accommodating evolving technologies and research requirements.
3. Assess which research capabilities and infrastructure should be specialized, shared, duplicated, or adaptable across multiple facilities to balance access, operational needs, redundancy, and long-term flexibility.
4. Apply lessons from three distinct campus projects to develop a coordinated planning approach that aligns researchers, academic leadership, facilities teams, designers, and industry partners around a scalable robotics research ecosystem.