SMART INSTRUMENTS FOR REMOTE EXPLORATION
I'm leading the TextureCam project to integrate automatic image analysis into a Field Programmable Gate Array. This will permit automatic image understanding by remote robotic explorers like spacecraft and planetary rovers. We aim to provide these robots the ability to identify basic science features so that they can make simple decisions about where to collect data and what to transmit to Earth. Image: automatic classification of Mars Exploration Rover image to find rocks. Original credit NASA/JPL.
- D. R. Thompson, Robert O. Green, Didier Keymeulen, Sarah Lundeen, Yasha Mouradi , Rebecca Castano, Steve A.
Chien, Rapid spectral cloud screening onboard aircraft and spacecraft. IEEE Transactions on Geoscience and Remote Sensing, 2014 (accepted) .
- K. L. Wagstaff, D. R. Thompson, W. Abbey, A. Allwood, D. L. Bekker, N. A. Cabrol, T. Fuchs, and K. Ortega. Smart, texture-sensitive instrument classification for in situ rock and layer analysis. Geophysical Research Letters, vol. 40, 2013.
- D. R. Thompson, N. A. Cabrol, M. Furlong, C. Hardgrove, B. K. H. Low, J. Moersch, D. S. Wettergreen. Adaptive Sensing of Time Series with Application to Remote Exploration ICRA 2013. (PDF)
- G. Foil, D. R. Thompson, W. Abbey, D. S. Wettergreen. Probabilistic Surface Classification for Rover Instrument Targeting. IEEE Conference On Intelligent Robots and Systems (IROS) 2013.
NEXT-GENERATION MISSION OPERATIONS FOR PRIMITIVE BODIES
Future primitive body exploration missions may need to revise trajectories and observation plans to quickly characterize the target for safe, effective observations. However, light time delays for communication with Earth may be tens of minutes to hours. When appropriate, time-critical decisions could be automated and shifted to the spacecraft for immediate access to instrument data. Mirrored planning systems on both sides of the light-time gap permit fluid transfer of authority as needed. Image: automatic detection of Hartley 2 comet plumes. Original image credit: NASA/JPL/UMD.
- D. R. Thompson, M. Bunte, R. Castano, S. Chien, R. Greeley. Image Processig Onboard Spacecraft for Autonomous Plume Detection. Planetary and Space Science Vol. 62, 2012. p. 153-159.(PDF)
- D. R. Thompson, J. C. Castillo-Rogez, S. A. Chien, R. Doyle, T. Estlin, D. Mclaren. Agile Science Operations: A New Approach for Primitive Bodies Exploration. SpaceOps, 2012. Stockholm.
- D. R. Thompson, S. Chien, D. Tran, M. Bunte, R. Greeley. Autonomous Onboard Science Data Analysis for Comet Missions. i-SAIRAS 2012. (PDF)
REAL TIME DATA MINING FOR PETASCALE SCIENCE INSTRUMENTS
New radio astronomy instruments like the Square Kilometre Array (SKA) will generate petabyte data volumes. These investigations would benefit from real time anomaly detection and data mining to identify key features of interest. We're currently investigating adaptive resource allocation strategies and cost-sensitive computing to identify transient radio sources in radio astronomy data.
- K. Wagstaff, N. Lanza, D. R. Thompson, T. Dietterich and M. Gilmore. Guiding Scientific Discovery with Explanations. Assoc. for the Advancement of Artificial Intelligence (AAAI) 2013.
- C. Trott., S. J. Tingay, R. B. Wayth, D. R. Thompson, A. T. Deller, W. F. Brisken, K. L. Wagstaff, W. A. Majid, S. Burke-Spolaor, J-P R. Macquart, D. Palaniswamy. A framework for interpreting fast radio transient search experiments: application to the V-FASTR experiment. The Astrophysical Journal 2013 (in press) (preprint PDF)
- D. R. Thompson, W. F. Brisken, A. T. Deller, W. A. Majid, S. Burke-Spolaor, S. J. Tingay, K. L. Wagstaff, and Randall B. Wayth. Real time adaptive event detection in astronomical data streams: lessons from the Very Long Baseline Array. IEEE Intelligent Systems 2013 (in press).(Preprint PDF)
- R. Wayth, S. J. Tingay, A. Deller, W. F. Brisken, D. R. Thompson, K. Wagstaff, and W. Majid. Limits on the event rates of fast radio transients from the V-FASTR experiment. The Astrophysical Journal Letters 753:L36 2012.(PDF)
Statistical models of the environment can tell explorer robots where to travel, what samples to collect and what data to return to scientists. Much of my work aims to ground autonomous science decisions by remote explorers in formal principles of information theory, active learning and experimental design.
- D. R. Thompson, N. A. Cabrol, M. Furlong, C. Hardgrove, B. K. H. Low, J. Moersch, D. S. Wettergreen. Adaptive Sensing of Time Series with Application to Remote Exploration. International Conference on Robotics and Automation, 2013 (PDF).
- B. K. H. Low, J. Chien, J. Dolan, S. Chien, D. R. Thompson. Decentralized Active Robotic Exploration and Mapping for Probabilistic Field Classification in Environmental Sensing. The Eleventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2012.
- D. Hayden, S. Chien, D. R. Thompson, R. Castano. Using Clustering and Metric Learning to Improve Science Return of Remote Sensed Imagery. ACM Transactions on Intelligent Systems , Vol. 3, No. 3, 2011. (PDF)
- D. R. Thompson, D. Wettergreen, and F. Calderon P. Autonomous Science for Large-Scale Robotic Survey.Journal of Field Robotics, Vol. 28, No. 4, July/Aug 2011.(PDF)
AUTOMATIC SPECTRAL ANALYSIS FOR REMOTE SENSING
Much of my work involves data mining on spectral images to automatically draft maps and characterize science phenomena. Image courtesy NASA/JPL.
- D. R. Thompson, M. de la Torre Juarez, C. M. Barker, J. Holeman, S. Lundeen, S. Mulligan, T. H. Painter, E. Podest, F. C. Seidel, E. Ustinov. Airborne imaging spectroscopy to monitor the evolution of urban mosquito microhabitats. Remote Sensing of Environment, Vol. 137, Oct. 2013.
- D. R. Thompson, B. Bornstein, S. Chien, S. Schafffer, D. Tran, B. Bue, R. Castano, D. Gleeson, A. Noell, Autonomous Spectral Discovery and Mapping onboard the EO-1 Spacecraft. IEEE Transactions on Geoscience and Remote Sensing , Vol. 51 No. 6, June 2013. (Preprint PDF)
- D. R. Thompson, L. Mandrake, R. O. Green, S. Chien, A Case Study of Subpixel Target Detection in Multimodal and Outlier-contaminated Scenes IEEE Geoscience and Remote Sensing Letters. (Preprint PDF)
- M. Gilmore, D. R. Thompson, L. J. Anderson, N. Karamzadeh, L. Mandrake, R. Castano. Superpixel segmentation for analysis of hyperspectral datasets, with application to CRISM data, M3 data and Ariadnes Chaos, Mars. Journal of Geophysical Research, Vol. 116, E07001, 2011.
- D. R. Thompson, L. Mandrake, M. S. Gilmore and R. Castano, Superpixel Endmember Detection. Transactions on Geoscience and Remote Sensing, 48(11): 4023-4033, Nov. 2010.
20TH CENTURY CHAMBER MUSIC
A relatively new music craze. I'm a big fan of the French Impressionists (Ravel, Debussy) although I've recently investigated some more modern stuff. Bartok's string quartets are my all-time favorite.