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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
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
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:
Dramatically increases the science per fixed downlink by
enabling downlink of the highest priority science data.
Enables study of short-lived science events (such as volanic
eruptions, dust storms, etc.)
Reduces downtime lost to anomalies due to robust execution
enabled by autonomy software.
Reduces instrument setup time by using autonomy software take
advantage of execution information to streamline operations.
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:
Initially, ASE has a list of science targets to monitor that
have been sent as high-level goals from the ground.
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.
During execution of this plan, the EO-1 spacecraft images Mt.
Etna with the Hyperion instrument.
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.
The SCL software executes the CASPER generated plans in
conjunction with several autonomy elements.
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
