1 citations · 1 across the 5 of their papers we have counts for
6 papers
DART-S: Reachability-Audited Active-Suspension Preconditioning for Off-Road Vehicle Jumps
Yu Hu, Fangzhou Zhao, Liang Chen +7
Airborne torque reaction cannot recover takeoff errors beyond the wheel angular-momentum budget. DART-S applies ramp-face suspension preconditioning to change pitch, pitch rate, an…
DART: Dual-Axis Airborne Reachability-Gated Torque-Reaction for Off-Road Vehicle Jumps
Yu Hu, Fangzhou Zhao, Mingyuan Sang +7
Traversing crests, ledges, and ditches at high speed often launches vehicles into the air, and a mishandled landing presents a substantial crash hazard. We show that the airborne p…
ROD: RGB-Only Fast and Efficient Off-road Freespace Detection
Tong Sun, Hongliang Ye, Jilin Mei +4
Off-road freespace detection is more challenging than on-road scenarios because of the blurred boundaries of traversable areas. Previous state-of-the-art (SOTA) methods employ mult…
WildOcc: A Benchmark for Off-Road 3D Semantic Occupancy Prediction
Heng Zhai, Jilin Mei, Chen Min +3
3D semantic occupancy prediction is an essential part of autonomous driving, focusing on capturing the geometric details of scenes. Off-road environments are rich in geometric info…
Proto-OOD: Enhancing OOD Object Detection with Prototype Feature Similarity
Junkun Chen, Jilin Mei, Liang Chen +3
Neural networks that are trained on limited category samples often mispredict out-of-distribution (OOD) objects. We observe that features of the same category are more tightly clus…
TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentation
Junbao Zhou, Jilin Mei, Pengze Wu +4
In autonomous driving, 3D LiDAR plays a crucial role in understanding the vehicle's surroundings. However, the newly emerged, unannotated objects presents few-shot learning problem…