Model-based planning of optimal sensor placements for inspection

We report a system for sensor planning, GASP, which is used to compute the optimal positions for inspection tasks using known imaging sensors and feature-based object models. GASP (general automatic sensor planning) uses a feature inspection representation (the FIR), which contains the explicit solution for the simplest sensor positioning problem. The FIR is generated off-line, and is exploited by GASP to compute on-line plans for more complex tasks, called inspection scripts. Viewpoint optimality is defined as a function of feature visibility and measurement reliability. Visibility is computed using an approximate model. Reliability of inspection depends on both the physical sensors acquiring the images and on the processing software; therefore we include both these components in a generalized sensor model. These predictions are based on experimental, quantitative assessment. We show how these are computed for a real generalized sensor, which includes a 3-D range imaging system, and software performing robust outlier removal, surface segmentation, object location and surface fitting. Finally, we demonstrate a complete inspection session involving 3-D object positioning, planning optimal position inspection, and feature measurement from the optimal viewpoint.