45 citations · 100 across the 10 of their papers we have counts for
10 papers
UniWorld: Autonomous Driving Pre-training via World Models
Chen Min, Dawei Zhao, Liang Xiao +2
In this paper, we draw inspiration from Alberto Elfes' pioneering work in 1989, where he introduced the concept of the occupancy grid as World Models for robots. We imbue the robot…
Contrastive Label Disambiguation for Self-Supervised Terrain Traversability Learning in Off-Road Environments
Hanzhang Xue, Xiaochang Hu, Rui Xie +4
Discriminating the traversability of terrains is a crucial task for autonomous driving in off-road environments. However, it is challenging due to the diverse, ambiguous, and platf…
Traversability Analysis for Autonomous Driving in Complex Environment: A LiDAR-based Terrain Modeling Approach
Hanzhang Xue, Hao Fu, Liang Xiao +3
For autonomous driving, traversability analysis is one of the most basic and essential tasks. In this paper, we propose a novel LiDAR-based terrain modeling approach, which could o…
RDMNet: Reliable Dense Matching Based Point Cloud Registration for Autonomous Driving
Chenghao Shi, Xieyuanli Chen, Huimin Lu +3
Point cloud registration is an important task in robotics and autonomous driving to estimate the ego-motion of the vehicle. Recent advances following the coarse-to-fine manner show…
ORFD: A Dataset and Benchmark for Off-Road Freespace Detection
Chen Min, Weizhong Jiang, Dawei Zhao +4
Freespace detection is an essential component of autonomous driving technology and plays an important role in trajectory planning. In the last decade, deep learning-based free spac…
Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders
Chen Min, Xinli Xu, Dawei Zhao +3
Current perception models in autonomous driving heavily rely on large-scale labelled 3D data, which is both costly and time-consuming to annotate. This work proposes a solution to…