This article examines the selection of a robot's actuation and sensing hardware to minimize
the cost of that design while ensuring that the robot is capable of carrying out a plan to …

We address problems underlying the algorithmic question of automating the co-design of
robot hardware in tandem with its apposite software. Specifically, we consider the impact …

Whether a robot can perform some specific task depends on several aspects, including the
robot's sensors and the plans it possesses. We are interested in search algorithms that treat …

Recent research has examined algorithms to minimize robots' resource footprints. The class
of combinatorial filters (discrete variants of widely-used probabilistic estimators) has been …

Combinatorial filters are discrete structures for modeling and reasoning about robotic
systems. Such filters are of interest not only because of the potential for reduction of the …

Assuming one wants to design the most cost-effective robot for some task, how difficult is it to
choose the robot's actuators? This paper addresses that question in algorithmic terms …

State minimization of combinatorial filters is a fundamental problem that arises, for example,
in building cheap, resource-efficient robots. But exact minimization is known to be NP-hard …

Motivated by the need for tools to aid in the design of effective robots, we examine how to
determine the role that particular sensing and actuator resources play in enabling a robot to …

Currently there do not exist general-purpose robots, and the procedures by which robots are
designed are often ad hoc. Additionally, designers must deal with considerations including …

Reduction of combinatorial filters involves compressing state representations that robots
use. Such optimization arises in automating the construction of minimalist robots. But exact …