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Abstracr-Solutions for four different pose estimation problems are presented. Closed form least-squares solutions are given to the over constrained ZD-ZD and 3-D-3-D pose estimation problems. A globally convergent iterative technique is given for the 2-D perspective projection -3-D pose estimation problem. A simplified linear solution and a robust solution to the 2-D perspective projection-ZD perspective projection pose estimation problem are also given. Simulation experiments consisting of millions of hials having varying numbers of pairs of corresponding points, varying signal to noise ratio (SNR) with either Gaussian or uniform noise provide data suggesting that accurate inference of rotation and translation with noisy data may require corresponding point data sets having hundreds of corresponding point pairs when the SNR is less than 40 dB. The experiment results also show that robust technique can suppress the effect of blunder data that come from outliers or mismatched points.

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