Machine learning for autonomous field data collection


The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by NSF. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim.

This project will make a significant contribution toward the support of future workers in geology. Understanding how geologists reason, plan to collect new data, consider three-dimensional spatial relations, and evaluate uncertainty are critically important for supporting scientists working on applied problems, such as natural resource exploration. This project will enhance existing efforts in geology to collect data using robot drones. Drones allow access to important areas of the world too dangerous to access in person and not visible from satellite or plane. The project will use machine learning to incorporate expert knowledge into drone flights to support effective autonomous data collection. The data will yield improved geological understanding of an important fault system. Findings from the project will improve understanding of uncertainty in volumes and thus improve our understanding of earthquakes and the analyses of petroleum workers. Understanding how expert geologists reason will support new exploration and mapping strategies for human-robot teams working in natural environments. The collaborative efforts of the interdisciplinary team will advance the fields of cognitive science, geology, and machine learning. The integration of cognitive science, robotics, and geology will develop new approaches to field work with human-autonomous systems teams that are faster and more effective than any either human or autonomous system would be acting alone.

This entry was posted in Uncategorized. Bookmark the permalink.