  The Michigan Robotics MBot is a low-cost mobile robot platform that has been
used to train over 1,400 students in autonomous navigation since 2014 at the
University of Michigan and our collaborating colleges. The MBot platform was
designed to meet the needs of teaching robotics at scale to match the growth of
robotics as a field and an academic discipline. Transformative advancements in
robot navigation over the past decades have led to a significant demand for
skilled roboticists across industry and academia. This demand has sparked a
need for robotics courses in higher education, spanning all levels of
undergraduate and graduate experiences. Incorporating real robot platforms into
such courses and curricula is effective for conveying the unique challenges of
programming embodied agents in real-world environments and sparking student
interest. However, teaching with real robots remains challenging due to the
cost of hardware and the development effort involved in adapting existing
hardware for a new course. In this paper, we describe the design and evolution
of the MBot platform, and the underlying principals of scalability and
flexibility which are keys to its success.
