2 citations · 2 across the 8 of their papers we have counts for
8 papers
DTP-Attack: A decision-based black-box adversarial attack on trajectory prediction
Jiaxiang Li, Jun Yan, Daniel Watzenig +1
Trajectory prediction systems are critical for autonomous vehicle safety, yet remain vulnerable to adversarial attacks that can cause catastrophic traffic behavior misinterpretatio…
MAP: End-to-End Autonomous Driving with Map-Assisted Planning
Huilin Yin, Yiming Kan, Daniel Watzenig
In recent years, end-to-end autonomous driving has attracted increasing attention for its ability to jointly model perception, prediction, and planning within a unified framework.…
Thermal-LiDAR Fusion for Robust Tunnel Localization in GNSS-Denied and Low-Visibility Conditions
Lukas Schichler, Karin Festl, Selim Solmaz +1
Despite significant progress in autonomous navigation, a critical gap remains in ensuring reliable localization in hazardous environments such as tunnels, urban disaster zones, and…
WS-DETR: Robust Water Surface Object Detection through Vision-Radar Fusion with Detection Transformer
Huilin Yin, Pengyu Wang, Senmao Li +2
Robust object detection for Unmanned Surface Vehicles (USVs) in complex water environments is essential for reliable navigation and operation. Specifically, water surface object de…
Spatiotemporal Attention-Augmented Inverse Reinforcement Learning for Multi-Agent Task Allocation
Huilin Yin, Zhikun Yang, Linchuan Zhang +1
Adversarial inverse reinforcement learning (IRL) for multi-agent task allocation (MATA) is challenged by non-stationary interactions and high-dimensional coordination. Unconstraine…
A Cost-Effective Approach to Smooth A* Path Planning for Autonomous Vehicles
Lukas Schichler, Karin Festl, Selim Solmaz +1
Path planning for wheeled mobile robots is a critical component in the field of automation and intelligent transportation systems. Car-like vehicles, which have non-holonomic const…
Segment-Anything Models Achieve Zero-shot Robustness in Autonomous Driving
Jun Yan, Pengyu Wang, Danni Wang +3
Semantic segmentation is a significant perception task in autonomous driving. It suffers from the risks of adversarial examples. In the past few years, deep learning has gradually…
Random Network Distillation Based Deep Reinforcement Learning for AGV Path Planning
Huilin Yin, Shengkai Su, Yinjia Lin +3
With the flourishing development of intelligent warehousing systems, the technology of Automated Guided Vehicle (AGV) has experienced rapid growth. Within intelligent warehousing e…