3 papers
cs.RO2026
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…
cs.RO2026
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…
cs.RO2025
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…