Abstract
Speckle velocimetry is investigated as a means of determining odometry data with potential for application on autonomous robotic vehicles. The technique described here relies on the integration of translation measurements made by normalized cross-correlation of speckle patterns to determine the change in position over time. The use of objective (non-imaged) speckle offers a number of advantages over subjective (imaged) speckle, such as a reduction in the number of optical components, reduced modulation of speckles at the edges of the image, and improved light efficiency. The influence of the source/detector configuration on the speckle translation to vehicle translation scaling factor for objective speckle is investigated using a computer model and verified experimentally. Experimental measurements are presented at velocities up to 80 mm s(-1) which show accuracy better than 0.4%.
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