1 code implementation • 5 Mar 2024 • Jay Patrikar, Joao Dantas, Brady Moon, Milad Hamidi, Sourish Ghosh, Nikhil Keetha, Ian Higgins, Atharva Chandak, Takashi Yoneyama, Sebastian Scherer
In total, TartanAviation provides 3. 1M images, 3374 hours of Air Traffic Control speech data, and 661 days of ADS-B trajectory data.
no code implementations • 14 Dec 2023 • Yafei Hu, Quanting Xie, Vidhi Jain, Jonathan Francis, Jay Patrikar, Nikhil Keetha, Seungchan Kim, Yaqi Xie, Tianyi Zhang, Shibo Zhao, Yu Quan Chong, Chen Wang, Katia Sycara, Matthew Johnson-Roberson, Dhruv Batra, Xiaolong Wang, Sebastian Scherer, Zsolt Kira, Fei Xia, Yonatan Bisk
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.
no code implementations • 4 Apr 2023 • Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas, Rohan Baijal, Ian Higgins, Sebastian Scherer, Jean Oh
In this work, we propose Social Robot Tree Search (SoRTS), an algorithm for the safe navigation of mobile robots in social domains.
no code implementations • 26 Sep 2022 • Sourish Ghosh, Jay Patrikar, Brady Moon, Milad Moghassem Hamidi, Sebastian Scherer
Detect-and-Avoid (DAA) capabilities are critical for safe operations of unmanned aircraft systems (UAS).
no code implementations • 22 Nov 2021 • Thiago A. Rodrigues, Jay Patrikar, Natalia L. Oliveira, H. Scott Matthews, Sebastian Scherer, Constantine Samaras
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.
1 code implementation • 31 May 2021 • Arnav Choudhry, Brady Moon, Jay Patrikar, Constantine Samaras, Sebastian Scherer
Computing the CVaR on the risk-space distribution provides a metric that can evaluate the overall risk of a flight before take-off.