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CL 01-0573

Autonomous
Sciencecraft
Experiment

Eo1 Imaging Earth

Co-Winner: 2005 NASA Software of the Year Award

Mission Status: Check on the latest totals of ASE

Background

ASE Concept Image

Since the dawn of the space age, unmanned spacecraft have flown blind with little or no ability to make autonomous decisions based on the content of the data they collect. The Autonomous Sciencecraft Experiment (ASE) is operating onboard the Earth Observing-1 mission since 2003. The ASE software uses onboard continuous planning, robust task and goal-based execution, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. This software demonstrates the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data.

AI Technology

The ASE onboard flight software includes several autonomy software components:

Onboard science algorithms
that analyzes the image data to detect trigger conditions such as science events, interesting features, changes relative to previous observations, and cloud detection for onboard image editing
Robust execution management software
using the Spacecraft Command Language (SCL) package to enable event-driven processing and low-level autonomy
Continuous Activity Scheduling Planning Execution and Replanning (CASPER) software
that replan activities, including downlink, based on science observations in the previous orbit cycles
Europa Ice
Tracking Europa Surface Ice

The onboard science algorithms analyzes the images to extract static features and detect changes relative to previous observations. Applied to EO-1 Hyperion data, these algorithms automatically identify regions of interest including regions of change (such as flooding, ice melt, and lava flows). Using these algorithms onboard enables retargeting and search, e.g., retargeting the instrument on a subsequent orbit cycle to identify and capture the full extent of a flood. On future interplanetary space missions, onboard science analysis will enable capture of short-lived science phenomena at the finest time-scales without overwhelming onboard memory or downlink capacities. Examples include: eruption of volcanoes on Io, formation of jets on comets, and phase transitions in ring systems. Generation of derived science products (e.g., boundary descriptions, catalogs) and change-based triggering will also reduce data volumes to a manageable level for extended duration missions that study long-term phenomena such as atmospheric changes at Jupiter and flexing and cracking of the ice crust on Europa.

The onboard planner (CASPER) generates mission operations plans from goals provided by the onboard science analysis module. The model-based planning algorithms enables rapid response to a wide range of operations scenarios based on a deep model of spacecraft constraints, including faster recovery from spacecraft anomalies. The onboard planner accepts as inputs the science and engineering goals and ensure high-level goal-oriented behavior.

The robust execution system (SCL) accepts the CASPER-derived plan as an input and expands the plan into low-level commands. SCL monitors the execution of the plan and has the flexibility and knowledge to perform event-driven commanding to enable local improvements in execution as well as local responses to anomalies.

Problem

Constrained downlink resources limit the science return of current and future space missions.

Impact

IO Volcano
Short-Lived Eruption on Io

Demonstration of these capabilities in a flight environment opens up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology. This technology:



Status

Mission Last Week Yesterday Upcoming
Images Taken 54683 103 20 32
     Sensorweb 4774 9 0 0
Science Scenarios Executed 1470 0 0 0
     Positive Triggers 257 0 0
Ground Contacts 50232 103 16 27
     X-Band 18609 39 7 10
     S-Band 31623 64 9 17

Description

A typical ASE demonstration scenario involves monitoring of active volcano regions such as Mt. Etna in Italy. Hyperion data have been used in ground-based analysis to study this phenomenon. The ASE concept is applied as follows:

  1. Initially, ASE has a list of science targets to monitor that have been sent as high-level goals from the ground.
  2. As part of normal operations, CASPER generates a plan to monitor the targets on this list by periodically imaging them with the Hyperion instrument. For volcanic studies, the IR and near IR bands are used.
  3. During execution of this plan, the EO-1 spacecraft images Mt. Etna with the Hyperion instrument.
  4. The onboard science algorithms analyzes the image and detects a fresh lava flow. Based on this detection the image is downlinked. Had no new lava flow been detected, the science software would generate a goal for the planner to acquire the next highest priority target in the list of targets. The addition of this goal to the current goal set triggers CASPER to modify the current operations plan to include numerous new activities in order to enable the new science observation.
  5. The SCL software executes the CASPER generated plans in conjunction with several autonomy elements.
  6. This cycle is then repeated on subsequent observations.

Publications

The EO-1 Autonomous Sciencecraft R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau Small Satellite Conference. Logan, UT. August 2007 + PDF CL#07-2056
Mission Operations of Earth Observing-1 with Onboard Autonomy G. Rabideau, D. Tran, S. Chien, B. Cichy, R. Sherwood, D. Mandel, S. Frye, S. Shulman, J. Szwaxzkowski, D. Boyer, J. Van Gassbeck IEEE International Conference on Space Mission Challenges for Information Technology. Pasadena, CA. July 2006 + PDF CL#06-2265
Enhancing Science and Automating Operations Using Onboard Autonomy R. Sherwood, S. Chien, D. Tran, A. Davies, R. Castano, G. Rabideau, D. Mandel, S. Frye, S. Shulman, J. Szwaxzkowski International Conference on Space Operations (SpaceOps 2006). Rome, Italy. June 2006 + PDF CL#06-1528
Autonomous Science Agents and Sensor Webs: EO-1 and Beyond R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau IEEE Aerospace Conference (IAC 2006). Big Sky, MT. March 2006 + PDF CL#05-3565
Using Autonomy Flight Software to Improve Science Return on Earth Observing One S. Chien, R. Sherwood, D. Tran, B. Cichy, G. Rabideau, R. Castano, A. Davies, D. Mandl, S. Frye, B. Trout, S. Shulman, D. Boyer Journal of Aerospace Computing, Information, and Communication . April 2005 . + PDF CL#05-0079
Lessons Learned from Autonomous Sciencecraft Experiment S. Chien, R. Sherwood, D. Tran, B. Cichy, G. Rabideau, R. Castano, A. Davies, D. Mandl, S. Frye, B. Trout, J. D'Agostino, S. Shulman, D. Boyer, S. Hayden, A. Sweet, S. Christa Autonomous Agents and Multi-Agent Systems Conference (AAMAS 2005). Utrecht, Netherlands. July 2005 + PDF CL#05-1122
The ST6 Autonomous Sciencecraft Experiment R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau IEEE Aerospace Conference. Big Sky, MT. March 2005
Safe Agents in Space: Preventing and Responding to Anomalies in the Autonomous Sciencecraft Experiment D. Tran, S. Chien, G. Rabideau, B. Cichy Autonomous Agents and Multi-Agent Systems Conference International Workshop on Safety and Security in Multi-Agent Systems. (AAMAS 2005). Utrecht, Netherlands. July 2005 + PDF CL#05-1321
Onboard Autonomy on the Earth Observing One Mission S. Chien, R. Sherwood , et. al AIAA Intelligent Systems Technical Conference. Chicago, IL. September 2004
Validating the Autonomous EO-1 Science Agent B. Cichy, S. Chien, S. Schaffer, D. Tran, G. Rabideau, R. Sherwood International Workshop on Planning and Scheduling for Space (IWPSS 2004). Darmstadt, Germany. June 2004 + PDF CL#04-1273
Mission Operations with Autonomy: A preliminary report for Earth Observing-1 G. Rabideau, S. Chien, R. Sherwood, D. Tran, B. Cichy, D. Mandl, S. Frye, S. Shulman, R. Bote, J. Szwaczkowski, D. Boyer, J. Van Gaasbeck International Workshop on Planning and Scheduling for Space (IWPSS 2004). Darmstadt, Germany. June 2004 + PDF CL#04-0665
Safe Agents in Space: Lessons from the Autonomous Sciencecraft Experiment R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau Australian Joint Conference on Artificial Intelligence. Cairns, Australia. December 2004
Operating the Autonomous Sciencecraft Experiment R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau International Conference on Space Operations (SpaceOps 2004). Montreal, Canada. May 2004
Preliminary Results of the Autonomous Sciencecraft Experiment R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau IEEE Aerospace Conference. Big Sky, MT. March 2004
Flight Software Issues in Onboard Automated Planning: Lessons Learned on EO-1 D. Tran, S. Chien, G. Rabideau, B. Cichy International Workshop on Planning and Scheduling for Space (IWPSS 2004). Darmstadt, Germany. June 2004 + PDF CL#04-0901
Autonomous Science on the EO-1 Mission S. Chien, R. Sherwood, D. Tran, R. Castano, B. Cichy, A. Davies, G. Rabideau, N. Tang, M. Burl, D. Mandl, S. Frye, J. Hengemihle, J. Agostino, R. Bote, B. Trout, S. Shulman, S. Ungar, J. Van Gaasbeck, D. Boyer, M. Griffin, H. Burke, R. Greeley, T. Doggett, K. Williams, V. Baker, J. Dohm International Symposium on Artificial Intelligence, Robotics, and Automation in Space (i-SAIRAS 2003). Nara, Japan. May 2003 CL#03-0787
Software Demonstration: Autonomous Science Analysis, Planning, and Execution on the EO-1 Mission R. Sherwood, S. Chien, D. Tran, R. Castano, B. Cichy, A. Davies, G. Rabideau, N. Tang, M. Burl, D. Mandl, S. Frye, J. Hengemihle, J. D'Augustino, R. Bote, B. Trout, S. Shulman, S. Ungar, J. Van Gaasbeck, D. Boyer, M. Griffin, H. Burke, R. Greeley, T. Doggett, K. Williams, V. Baker, J. Dohm 13th International Conference on Automated Planning and Scheduling (ICAPS 2003). Trento, Italy. June 2003
Autonomous Science on the EO-1 Mission R. Sherwood NASA and Argentina's National Commision of Space Activities: Morning Constellation Workshop. Buenos Aires, Argentina. December 2003
Next Generation Autonomous Operations on a Current Generation Satellite R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau 5th International Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO 2003). Pasadena, CA. July 2003 CL#03-1398
The Autonomous Sciencecraft Experiment R. Sherwood, S. Chien, R. Castano, G. Rabideau IEEE 2003 Aerospace Conference. Big Sky, MT. March 2003
The Techsat-21 Autonomous Space Science Agent S. Chien, R. Sherwood, G. Rabideau, R. Castano, A. Davies, M. Burl, R. Knight, T. Stough, J. Roden, P. Zetocha, R. Wainwright, J. Van Gaasbeck, P. Cappelaere, D. Oswald International Conference on Autonomous Agents (Agents 2002). Bologna, Italy. July 2002 + PDF CL#02-1413
ASC Science Report A. Davies, R. Greenley, K. Williams, V. Baker, J. Dohm, M. Burl, E. Mjolsness, R. Castano, T. Stough, J. Roden, S. Chien, R. Sherwood Interplanetary Network Directorate Technology and Science News . Issue 16 September 2002 . CL#02-2233
Autonomous Operations through Onboard Artificial Intelligence R. Sherwood, S. Chien, R. Castano, G. Rabideau International Conference on Space Operations (SpaceOps 2002). Houston, TX. Ocotober 2002
Spacecraft Autonomy using Onboard Processing for a SAR Constellation Mission R. Sherwood, S. Chien, R. Castano, G. Rabideau International Society for Photogrammetry and Remote Sensing Commission 1 Symposium International Workshop on Future Intelligent Earth Observing Satellites. (FIEOS@ISPRS 2002). Denver, CO. November 2002
Autonomous Planning and Scheduling on the TechSat 21 Mission R. Sherwood, S. Chien, R. Castano, G. Rabideau Australian Joint Conference on Artificial Intelligence. Canberra, Australia. December 2002
Automated Detection of Craters and Other Geological Features M. C. Burl, W. J. Merline, W. Colwell, E. B. Bierhaus, C. R. Chapman International Symposium on Artificial Intelligence, Robotics and Automation for Space. Montreal, CA. June 2001
Autonomous Visual Discovery M. Burl, D. Lucchetti SPIE AeroSense DMKDO. Orlando, FL. April 2000
Using Iterative Repair to Improve Responsiveness of Planning and Scheduling S. Chien, R. Knight, A. Stechert, R. Sherwood, G. Rabideau International Conference on Artificial Intelligence Planning Systems (AIPS 2000). Breckenridge, CO. April 2000

Contacts

Technology Provider (PI): Dr. Steve Chien
Steve.Chien at jpl.nasa.gov
818.393.5320
Experiment Manager: Robert Sherwood
Robert.Sherwood at jpl.nasa.gov
818.393.5378

Project Team

JPL: Steve Chien
Rob Sherwood
Becky Castano
Ashley Davies
Gregg Rabideau
Daniel Tran
Ben Cichy
Nghia Tang
Rachel Lee
Russell Knight
Steve Schaffer
NASA Goddard Space Flight Center: Dan Mandl
Stuart Frye (Mitretek)
Seth Shulman (Honeywell-TSI)
Joe Szwaczkowski (Honeywell-TSI)
Josh Bowman (Adnet)
Rob Bote
Interface and Control Systems: Darrell Boyer
Jim VanGaasbeck
Microtel: Bruce Trout
Nick Hengemihle
Jerry Hengemihle
the Hammers Company: Jeff D'Agostino
Kathie Blackman
Arizona State University: Ronald Greeley
Thomas Doggett
University of Arizona: Victor Baker
James Dohm
Felipe Ip
Center for Earth and Planetary Studies
National Air and Space Museum
Smithsonian Institute:
Kevin Williams

Sponsors

+ New Millennium Program




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