At the intersection of robotics, computational geometry, and manufacturing engineering, we have identified collection of research problems with near-term industrial applications. The common thread is robot systems with reduced intricacy in sensing and control (RISC), such as light beam sensors and parallel-jaw grippers. We conjecture that such systems, coupled with appropriate algorithms, are capable of recognizing and orienting a broad class of industrial parts. When compared with general-purpose robots, the resulting systems could be: (1) lower in cost, (2) more reliable, and (3) easier to reconfigure. The proposed hardware bears a close resemblance to existing "hard" automation; what is new is the application of computational methods for robust design and control of these systems, and more extensive use of simple sensors. By focusing on a small vocabulary of simple hardware, planning become computationally tractable and we can in some cases make guarantees about the existence of solutions. We borrowed the RISC acronym from computer architecture to acknowledge a common theme: identifying a minimal set of hardware primitives and matching these primitives with highly efficient software. In this paper, we review recent algorithms for locating, feeding, inserting and fixturing industrial parts. We discuss related work and propose a set of open problems for future research.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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