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Found 6 papers, 2 papers with code
TartanAviation: Image, Speech, and ADS-B Trajectory Datasets for Terminal Airspace Operations
In total, TartanAviation provides 3. 1M images, 3374 hours of Air Traffic Control speech data, and 661 days of ADS-B trajectory data.
Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis
Motivated by the impressive open-set performance and content generation capabilities of web-scale, large-capacity pre-trained models (i. e., foundation models) in research fields such as Natural Language Processing (NLP) and Computer Vision (CV), we devote this survey to exploring (i) how these existing foundation models from NLP and CV can be applied to the field of robotics, and also exploring (ii) what a robotics-specific foundation model would look like.
Learned Tree Search for Long-Horizon Social Robot Navigation in Shared Airspace
In this work, we propose Social Robot Tree Search (SoRTS), an algorithm for the safe navigation of mobile robots in social domains.
AirTrack: Onboard Deep Learning Framework for Long-Range Aircraft Detection and Tracking
Detect-and-Avoid (DAA) capabilities are critical for safe operations of unmanned aircraft systems (UAS).
Drone flight data reveal energy and greenhouse gas emissions savings for small package delivery
The adoption of Uncrewed Aerial Vehicles (UAVs) for last-mile deliveries will affect the energy productivity of package delivery and require new methods to understand the associated energy consumption and greenhouse gas (GHG) emissions.
CVaR-based Flight Energy Risk Assessment for Multirotor UAVs using a Deep Energy Model
Computing the CVaR on the risk-space distribution provides a metric that can evaluate the overall risk of a flight before take-off.
