LAUSR

In this paper, we present a patch-based direct visual odometry (DVO) that is robust to illumination changes at a sequence of stereo images. Illumination change violates the photo-consistency assumption and degrades the performance of DVO, thus, it should be carefully handled during minimizing the photometric error. Our approach divides an incoming image into several buckets, and patches inside each bucket own its unique affine illumination parameter to account for local illumination changes for which the global affine model fails to account, then it aligns small patches placed at temporal images. We do not distribute affine parameters to each patch since this yields huge computational load. Furthermore, we propose a prior weight as a function of the previous pose in a constant velocity model which implies that the faster a camera moves, the more likely it maintains the constant velocity model. Lastly, we verify that the proposed algorithm outperforms the global affine illumination model at the publicly available micro aerial vehicle and the planetary rover dataset which exhibit irregular and partial illumination changes due to the automatic exposure of the camera and the strong outdoor sunlight, respectively.