Real Time Data Mining for the Square Kilometre Array
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. (Image: Supernova remnant W28, courtesy of NRAO/AUI/NSF and Brogan et al.)
- D. R. Thompson, W. A. Majid, C. Reed, and K. L. Wagstaff. "Semi-supervised novelty detection with adaptive eigenbases, and application to radio transients," NASA Conference on Intelligent Data Understanding. October 2011. (Best Paper Award) (PDF)
- C. J. Reed, D. R. Thompson, W. A. Majid, and K. L. Wagstaff. "Real time machine learning to find fast transient radio anomalies: A semi-supervised approach combining detection and RFI excision." International Astronomical Union Symposium on Time Domain Astronomy, Oxford, UK. September 2011. (PDF)
- D. R. Thompson, W. Brisken, A. Deller, W. A. Majid, D. R. Thompson, S. Tingay, K. L. Wagstaff,R. Wayth "V-FASTR: Transient Detection on the Very Long Baseline Array, and Implications for the Square Kilometre Array" SKA 2011 Conference, Banff, Canada. July 2011. (PDF).
- D. R. Thompson, K. L. Wagstaff, A. Deller, W. Brisken, W. A. Majid, S. Tingay, R. Wayth , "Detection of Fast Transients with Multiple Stations: A Case Study with the Very Long Baseline Array," The Astrophysical Journal 735, 98. 2011. (preprint PDF).
- R. Wayth, W. Brisken, A. Deller, W. A. Majid, D. R. Thompson, S. Tingay, K. L. Wagstaff, "V-FASTR: The VLBA Fast Radio Transients Experiment." The Astrophysical Journal 735, 98. 2011. (arxiv preprint).
- K. L. Wagstaff, D. R. Thompson, and W. A. Majid, "Machine learning for real-time transient detection," International SKA Science and Engineering Meeting . March 2010.
- D. R. Thompson, K. L. Wagstaff, R. Wayth, A. Deller, and S. Tingay, "Machine learning for transient detection with radio arrays," AstroInformatics 2010 Conference (Jun. 2010)
- J-P Macquart and the CRAFT collaboration team. "Commensal Real-time ASKAP Fast Transients (CRAFT) Survey," PASA 2010.
Autonomous Remote Exploration
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, M. Bunte, R. Castaño, S. Chien, R. Greeley, Image ProcessingOnboard Spacecraft for AutonomousPlume Detection. Planetary and Space Science (in press).(PDF)
- 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 , 2011 (in press). (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)
- B. Bornstein, D. R. Thompson, S. Chien, R. Castano and B. Bue. Efficient Spectral Endmember Detection Onboard the EO-1 Spacecraft. IEEE WHISPERS 2011 (PDF).
- D. R. Thompson, M. Bunte, R. Castano, S. Chien, R. Greeley. Onboard Image Processing for Autonomous Spacecraft Detection of Volcanic Plumes. LPSC March 2011. (PDF)
- D. S. Hayden, S. Chien, D. R. Thompson, R. Castano. Using Onboard Clustering to Summarize Remotely Sensed Imagery. IEEE Intelligent Systems May 2010.
- D. R. Thompson, R. Castano and D. Wettergreen. Compression Ratio as Indicator of Scientist Preference For Rover Images. LPSC 2010 (PDF).
- D. R. Thompson, et al. Onboard Science Data Analysis: Implications for Future Missions. Planetary Science Decadal Survey, Community Whitepaper 2009 (PDF).
- D. R. Thompson. Domain-Informed Novelty Detection for Autonomous Exploration. IJCAI 2009 (PDF).
- D. Hayden, S. Chien, D. R. Thompson and R. Castano. Onboard Clustering of Aerial Data for Improved Science Return IJCAI Workshop on Artificial Intelligence in Space, 2009 (PDF).
- D. R. Thompson and N. Cabrol. Fast Texture Analysis for Autonomous Exploration. IJCAI Workshop on Artificial Intelligence in Space, 2009 (PDF).
- D. R. Thompson, T. Smith and D. Wettergreen. Information-Optimal Selective Data Return for Autonomous Rover Traverse Science and Survey. ICRA 2008 (PDF).
- D. R. Thompson and D. Wettergreen. A Tale of Two Rovers: Mission Scenarios for Kilometer-Scale Site Survey. ICRA Rover Workshop 2008 (Abstract) (Presentation).
- T. Smith, D. R. Thompson and D. Wettergreen. Generating Exponentially Smaller POMDP Models Using Conditionally Irrelevant Variable Abstraction. ICAPS 2007 (PDF).
- D. R. Thompson, T. Smith, and D. Wettergreen. Data Mining during Rover Traverse: From Images to Geologic Signatures. ISAIRAS 2005 (PDF).
Automatic Hyperspectral Image Analysis for Remote Sensing
I'm working on a JPL project to perform data mining on hyperspectral imagery to automatically draft maps and characterize science phenomena. In older work I've used spatial point processes to generate automatic maps of varying rock distributions in imagery from the Mars HiRise orbiting camera. The statistical models can identify patterns in features' clustering and spread that may not be visible to the naked eye. Image courtesy NASA/JPL.
- B. D. Bue, D. R. Thompson. Multiclass Continuous Correspondence Learning. NIPS Domain Adaptation Workshop, 2011.(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.
- B. Bue, D. R. Thompson, M. Gilmore and R. Castano. Metric Learning for Hyperspectral Image Segmentation. IEEE WHISPERS 2011(PDF)
- M. Bunte, D. R. Thompson, R. Castano, S. Chien, R. Greeley. Enabling Europa Science Through Onboard Feature Detection in Hyperspectral Images. LPSC March 2011 (PDF).
- D. R. Thompson, M. S. Gilmore, L. Mandrake and R. Castano, Automatic Detection of Mafics in M3 Radiance Images LPSC, 2011. (PDF).
- 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.
- L. Mandrake, D. R. Thompson, M. S. Gilmore and R. Castano, Automatic Neutral Region Detection with Superpixels. IEEE WHISPERS, June. 2010.
- L. Mandrake, D. R. Thompson, M. S. Gilmore and R. Castano, Hii-HAT: A Tool for Rapid Hyperspectral Inquiry. LPSC, Mar. 2010 (Poster).
- D. R. Thompson, L. Mandrake, M. S. Gilmore and R. Castano, Superpixel Segmentation for Endmember Detecion in Hyperspectral Images. AGU Fall Meeting, Dec. 2009 (Poster).
- D. R. Thompson, R. Castano and M. S. Gilmore, Sparse Superpixel Unmixing for Exploratory Analysis of CRISM Hyperspectral Images. IEEE Workshop on Hyperspectral Imagery and Signal Processing: Evolution in Remote Sensing, Aug. 2009 (PDF) (Presentation).
Stereo, Mapping, and Tracking
We want robots that can track a lot of objects simultaneously, target the interesting ones for analysis, and recognize things they've seen before. This is tough when you're constantly moving around to see features from different perspectives. However, doing it correctly can significantly improve remote sensing analyses.
- D. R. Thompson, W. Johnson, R. Kremens. Multiple-Frame Subpixel Wildfire Tracking. IEEE Geoscience and Remote Sensing Letters 2012 (in press) (preprint PDF).
- F. Calderon P., D. R. Thompson and D. Wettergreen. Autonomous Rover Reflectance Spectroscopy with Dozens of Targets. ISAIRAS 2008 (PDF).
- D. R. Thompson and D. Wettergreen. Multi-Object Detection with Multiple-View Expectation Maximization Clustering IROS, 2005 (PDF).
AEGIS Onboard Target Detection
I've been working on a team at JPL whose software provides automated target detection and response for the Mars Exploration Rovers (project website). Traditionally targets for remote sening (by cameras or spectrometers) are selected manually by operators in advance. This is less feasible for long-distance autonomous drives, where robots may visit terrain that is never seen by scientists. AEGIS allows the rover's flight software to automatically select features of interest and plan targeted observations in an opportunistic fashion. Image courtesy JPL/NASA/Caltech.
- T. Estlin, B. Bornstein, D. Gaines, R. C. Anderson, D. R. Thompson, M. Burl, R. Castano, M. Judd. AEGIS Automated targeting for MER Opportunity Rover. ACM Transactions on Intelligent Systems, 2011. (in press)
- T. Estlin, B. Bornstein, D. Gaines, D. R. Thompson, R. Castano, R. C. Anderson, C. de Granville, M. Burl, M. Judd, and S. Chien, AEGIS Automated Targeting for the MER Opportunity Rover, International Symposium on Artificial Intelligence, Robotics and Automation in Space (iSAIRAS), 2010.
- T. Estlin, R. Castano, B. Bornstein, D. Gaines, R. C. Anderson, C. de Granville, D. Thompson, M. Burl, M. Judd, and S. Chien, Automated Targeting for the MER Rovers , Proceedings of the 2009 Infotech, Aerospace AIAA Conference, Seattle, WA, April 2009.
- T. Estlin, R. Castano, R. C. Anderson, D. Gaines, B. Bornstein, C. de Granville, D. Thompson, M. Burl and M. Judd, Automated Targeting for the MER Rovers, Proceedings of the Space Mission Challenges for Information Technology Conference (SMC-IT 2009), Pasadena, CA, July 2009.
- T. Estlin, R. Castano, D. Gaines, R. C. Anderson, D. Gaines, B. Bornstein, C. de Granville, B. Yang, D. Thompson, and M. Judd, “A New Capability for Automated Targeting and Sampling using Remote Sensing Instruments on the MER Rovers,” Proceedings of AGU Fall Meeting, San Francisco December, 2008
Mission Planning for Intelligent Ocean Sensorwebs
I've worked on novel path planning strategies for tasking underactuated robot submarines, including "underwater gliders" and passive floats with depth control. Part of the challenge is designing an optimal mission that accounts for strong, dynamic ocean currents and tides. Another hurdle is developing the onboard autonomy to keep the glider safe between communications with shore. Among other projects, I worked to build a path/activity scheduling system as a part of the NSF Ocean Observatory Initiative's Atlantic Sensorweb. Glider image courtesy Rutgers University.
- K. Dahl, D. R. Thompson, D. McLaren, Y. Chao, S. Chien. Current-Sensitive Path Planning for an Underactuated Free-floating Ocean Sensorweb. International Conference on Robobics and Automated Systems, Dec. 2011 (PDF).
- O. Schofield and others incl. D. R. Thompson. A Regional Slocum Glider Network in the Mid-Atlantic Bight Leverages Broad Community Engagement Marine Technology Scociety Journal Vol. 195(11), Nov/Dec 2010, p. 185-195.
- Oscar Schofield and others incl. D. R. Thompson. "Automated Sensor Networks to Advance Ocean Science," EOS (EOS Transactions, American Geophysical Union). Vol. 91 No. 39, 28 Sept. 2010, p. 345-346.
- D. R. Thompson, S. Chien, Y. Chao, P. Li, B. Cahill, J. Levin, O. Schofield, A. Balasuriya, S. Petillo, M. Arrott, M. Meisinger. "Path Planning in Strong, Dynamic, Uncertain Currents," ICRA 2010 (PDF).
- D. R. Thompson, S. Chien, M. Arrott, A. Balasuriya, Y. Chao, P. Li, M. Meisinger, S. Petillo, O. Schofield. "Mission Planning in a Dynamic Ocean Sensorweb," ICAPS SPARK 2009. (PDF).
- D. R. Thompson, S. Chien, M. Arrott, A. Balasuriya, Y. Chao, P. Li, M. Meisinger, S. Petillo, O. Schofield. "A Mission Planning System for Underwater Gliders," ICAPS Applications Showcase 2009.
Robots in the Atacama Desert
I worked with a CMU project that ran some robot field tests in the driest place on Earth - the Atacama Desert in Northern Chile. There we simulated remote science operations as an analog to a search for life on another planet. During field operations autonomy software automatically identified lichens with the help of a fluorescence imager device.
- D. Wettergreen, M.D. Wagner, D. Jonak, V. Baskaran, M. Deans, S. Heys, D. Pane, T. Smith, J. Teza, D.R. Thompson, P. Tompkins, and C. Williams. Long-Distance Autonomous Survey and Mapping in the Robotic Investigation of Life in the Atacama Desert. ISAIRAS 2008 (PDF).
- T. Smith, D. R. Thompson, D. Wettergreen N. Cabrol, K. Warren-Rhodes and S. Weinstein. Life in the Atacama: Science Autonomy for Improved Data Quality. Journal of Geophysics Researchvol. 112, G04S03, Dec. 2007.
- D. R. Thompson, T. Smith and D. Wettergreen. Automatic Detection of Novel Biologic and Geologic Images in Atacama Desert Rover Traverse Imagery. LPSC 2006 (PDF).
- T. Smith, D. R. Thompson, S. Weinstein and D. Wettergreen. Automatic Chlorophyll Detection and Followup Applied to the Search for Life in the Atacama LPSC 2006 (PDF).
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.