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An appearance-based similarity measure for localizing a robot along a route is presented. This measure assesses the likelihood that the robot lies between a pair of positions where snapshot images were captured during training. The change in the scale parameter of matched SIFT features is used to determined whether the robot lies ahead or behind each snapshot. Experimental results in two different...
Local visual homing is the process of determining the direction of movement required to return an agent to a goal location by comparing the current image with an image taken at the goal, known as the snapshot image. One way of accomplishing visual homing is by computing the correspondences between features and then analyzing the resulting flow field to determine the correct direction of motion. Typically,...
A mobile robot can determine its rotation with respect to a goal position by comparing the image taken at the goal with the current image. Assuming that both images are omnidirectional, the current image can be shifted horizontally to determine the minimum difference with the goal image, and hence the rotation. The size of the region around the goal wherein this strategy succeeds is reduced by the...
In this paper, two global measures of image similarity are compared for use in topological localization of mobile robots. A catadioptric vision system was used as the sensor. Our localization system employs a discrete Bayes filter. Experimental results with real images of an office environment indicate the robot can localize itself from the memorized training images even with the modification of the...
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