6 accepted papers
This paper introduces a suspension-integrated tilting mechanism for narrow-track mobility robot platforms, offering a novel means of achieving commanded body tilt without departing from conventional suspension layouts. The architecture provides a two-degree-of-freedom roll path with inherent passive…
Self-supervised pre-training with masked autoencoders has shown promise for 3D perception, yet most approaches treat LiDAR point clouds in a geometry-agnostic manner. In this paper, we introduce Re-MAE, a geometry-aware self-supervised learning framework for LiDAR-based 3D object detection that expl…
In this paper, we present a novel study on a BEV (bird’s eye view) image-based lane tracking control system for an autonomous lane repainting robot. Our research introduces a cutting-edge lane detection method based on BEV images, leveraging row-anchor techniques to enhance precision and provide det…
Lane segmentation and Lane Keeping Assist System (LKAS) play a vital role in autonomous driving. While deep learning technology has significantly improved the accuracy of lane segmentation, real-world driving scenarios present various challenges. In particular, heavy rainfall not only obscures the r
The emergence of convolutional neural networks (CNNs) has led to significant advancements in various computer vision tasks. Among them, stereo matching is one of the most popular research areas that enables the reconstruction of 3D information, which is difficult to obtain with only a monocular came
As self-driving cars have been developed targeting level 4 and 5 autonomous driving, the capability of the vehicle to handle environmental effects has been considered importantly. The sensors installed on autonomous vehicles can be easily affected by blockages (e.g., rain, snow, dust, fog, and other