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RGB-Channel-based Illumination Robust SLAM Method

Peng Sun and Henry Y. K. Lau
Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong
Abstract—This paper provides an illumination robust direct monocular simultaneous localization and mapping (SLAM) method, which takes advantage of the RGB channel to enhance the lighting change invariance of the input frame series. By linearly combining the RGB channel, some illumination-insensitive components in the colour space are extracted and represented by three indicators in this paper. An optimization model is then provided to minimize the errors in these indicators using a Kalman filter (KF). These indicators serve to update the frames by keeping only the illumination-insensitive components. The illumination robust visual SLAM method based on these enhanced frames is thereby offered. In addition, the gradient magnitude is utilized to improve the distinctiveness of each pixel in the frame. Experiments on both artificial and natural datasets show that the provided method has a better illumination robustness than the state-of-the-art direct SLAM method. 

Index Terms—visual SLAM, illumination robustness, colour constancy

Cite: Peng Sun and Henry Y. K. Lau, "RGB-Channel-based Illumination Robust SLAM Method," Journal of Automation and Control Engineering, Vol. 7, No. 2, pp. 61-69, December, 2019. doi: 10.18178/joace.7.2.61-69
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