To address the 'sensor-bias problem', we propose a fast and flexible LiDAR augmentation method for the semantic segmentation task, called 'LiDomAug'. In our experiments, learning-based approaches aided with the proposed LiDomAug are less affected by the sensor-bias issue and achieve new state-of-the-art domain adaptation performances on SemanticKITTI and nuScenes dataset without the use of the target domain data.