A High Dynamic Range vision approach to outdoor localization

We propose a novel localization method for outdoor mobile robots using High Dynamic Range (HDR) vision technology. To obtain an HDR image, multiple images at different exposures is typically captured and combined. However, since mobile robots can be moving during a capture sequence, images cannot be fused easily. Instead, we generate a set of keypoints that incorporates those detected in each image. The position of the robot is estimated using the keypoint sets to match measured positions with a map. We conducted experimental comparisons of HDR and auto-exposure images, and our HDR method showed higher robustness and localization accuracy.