10 citations · 10 across the 4 of their papers we have counts for
4 papers
NEUROSYMLAND: Neuro-Symbolic Landing-Site Assessment for Robust and Edge-Deployable UAV Autonomy
Weixian Qian, Tianyi Yang, Sebastian Schroder +5
Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches often degrade under terrain vari…
Visual Marker Search for Autonomous Drone Landing in Diverse Urban Environments
Jiaohong Yao, Linfeng Liang, Yao Deng +3
Marker-based landing is widely used in drone delivery and return-to-base systems for its simplicity and reliability. However, most approaches assume idealized landing site visibili…
Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site Assessment
Weixian Qian, Tianyi Yang, Sebastian Schroder +5
Reliable assessment of safe landing sites in unstructured environments is essential for deploying Unmanned Aerial Vehicles (UAVs) in real-world applications such as delivery, inspe…
TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction
Yao Deng, Jiaohong Yao, Zhi Tu +3
Recent incidents with autonomous vehicles highlight the need for rigorous testing to ensure safety and robustness. Constructing test scenarios for autonomous driving systems (ADSs)…