  We consider the problem of co-designing embodied intelligence as a whole in a
structured way, from hardware components such as propulsion systems and sensors
to software modules such as control and perception pipelines. We propose a
principled approach to formulate and solve complex embodied intelligence
co-design problems, leveraging a monotone co-design theory. The methods we
propose are intuitive and integrate heterogeneous engineering disciplines,
allowing analytical and simulation-based modeling techniques and enabling
interdisciplinarity. We illustrate through a case study how, given a set of
desired behaviors, our framework is able to compute Pareto efficient solutions
for the entire hardware and software stack of a self-driving vehicle.
