Analysis of sensing errors for manufacturing geometric objects from senseddata

In this work we address the problem of manufacturing machine parts from sen sed data. Constructing geometric models for objects from sensed data is the intermediate step in a reverse engineering manufacturing system. Sensors a re usually inaccurate, providing uncertain sensed information. We construct geometric entities with uncertainty models from noisy measurements for the objects under consideration, and proceed to do reasoning on the uncertain geometries, thus, adding robustness to the construction of geometries from sensed data.