Computer-controlled dimensional inspection is typically performed with coordinate measuring machines (CMMs), which are very precise Cartesian robots that use touch probes to measure the coordinates of points on a workpiece's surfaces. Automatic planning and programming of inspection tasks with a CMM involve spatial reasoning, to determine how to orient the part on the CMM, which probes to use, how to orient the probes, and so on. This paper introduces the notions of accessibility and approachability, which are important for inspection planning, and describes two sets of implemented algorithms for computing accessibility information. One of these sets of algorithms performs exact computations on polyhedral objects and is relatively slow, whereas the other uses discrete approximations and achieves high speed by exploiting standard computer graphics hardware. The discretized algorithm has been tested on real-world parts, and is sufficiently fast for industrial applications.

This paper discusses a planner that generates automatically high-level programs (or plans) for inspecting mechanical parts with coordinate measuring machines. The system's input is a solid model of a toleranced part, and the output a collection of setups, probes and probe orientations associated with the surface features to be inspected. The problem is formulated as state space search. The state contains a collection of inspection plans, represented as a set of 4-tuples of the form (setup, probe, probe direction, surface feature). The initial plans may be invalid, or unnecessarily expensive. The state evolves through the application of operators, which impose geometric and optimization constraints so as to produce a valid and nearly optimal plan. The paper discusses the planner architecture and implementation, and presents experimental results.>

An overall strategy for inspection planning is discussed, and attention is focused on local and global accessibility cones and on algorithms for computing and clustering them. The direction-cone clusters serve to generate a minimal set of directions for inspecting a part. The algorithms are based primarily on the computation on Gaussian images and Minkowski (or sweeping) operations. Applications to computer vision and automatic machining are briefly presented.>