5 papers
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…
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…
AutoMT: A Multi-Agent LLM Framework for Automated Metamorphic Testing of Autonomous Driving Systems
Linfeng Liang, Chenkai Tan, Yao Deng +3
Autonomous Driving Systems (ADS) are safety-critical, where failures can be severe. While Metamorphic Testing (MT) is effective for fault detection in ADS, existing methods rely he…
A Step-by-Step Guide to Creating a Robust Autonomous Drone Testing Pipeline
Yupeng Jiang, Yao Deng, Sebastian Schroder +7
Autonomous drones are rapidly reshaping industries ranging from aerial delivery and infrastructure inspection to environmental monitoring and disaster response. Ensuring the safety…
Towards Robust Autonomous Landing Systems: Iterative Solutions and Key Lessons Learned
Sebastian Schroder, Yao Deng, Alice James +5
Uncrewed Aerial Vehicles (UAVs) have become a focal point of research, with both established companies and startups investing heavily in their development. This paper presents our…