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\n\n \n \n Chien, S.; Mclaren, D.; Doubleday, J.; Tran, D.; Tanpipat, V.; and Chitradon, R.\n\n\n \n \n \n \n \n Using Taskable Remote Sensing in a Sensor Web for Thailand Flood Monitoring.\n \n \n \n \n\n\n \n\n\n\n
Journal of Aerospace Information Systems (JAIS), 16(3): 107–119. 2019.\n
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@article{chien_jais2019_using,\n\ttitle = {Using Taskable Remote Sensing in a Sensor Web for Thailand Flood Monitoring},\n\tauthor = {S. Chien and D. Mclaren and J. Doubleday and D. Tran and V. Tanpipat and R. Chitradon},\n\tyear = 2019,\n\tjournal = {Journal of Aerospace Information Systems (JAIS)},\n\tvolume = 16,\n\tnumber = 3,\n\tpages = {107--119},\n\tdoi = {10.2514/1.I010672},\n\turl = {https://doi.org/10.2514/1.I010672},\n\tabstract = {Space-based assets have been integrated into a sensor web to monitor flooding in Thailand. In this approach, the moderate resolution imaging spectrometer data from the Terra and Aqua satellites are used to perform broad-scale monitoring for flood tracking at the regional level (250\\hspace{0.167em}\\hspace{0.167em}m/pixel) to generate flood detections/alerts. Based on these alerts, the Earth Observing-1 (EO-1) mission is autonomously tasked to acquire higher-resolution (10–30\\hspace{0.167em}\\hspace{0.167em}m/pixel) advanced land imager data, and a number of other assets have imagery automatically requested, with yet further assets requested only in a semiautomated fashion. Based on these alerts, these data are then automatically processed to derive products such as surface water extent and volumetric water estimates in shapefile formats to enable interpretation in geographic information systems. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. To date, Terra, Aqua, EO-1, Landsat, Ikonos, WorldView-1, WorldView-2, GeoEye-1, and Radarsat-2 have been used in some fashion in the sensor web. The overall autonomous detection, tasking, data acquisition, and processing sensor web framework are described, as well as ongoing work to extend to in situ sensor networks. How the automatic triggering of targeted higher-resolution observations enables higher temporal and spatial resolution tracking of flooding events is also documented.},\n\tclearance = {CL\\#18-7355},\n\teprint = {https://doi.org/10.2514/1.I010672},\n\torganization = {AIAA},\n\tproject = {tfs}\n}\n
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\n Space-based assets have been integrated into a sensor web to monitor flooding in Thailand. In this approach, the moderate resolution imaging spectrometer data from the Terra and Aqua satellites are used to perform broad-scale monitoring for flood tracking at the regional level (250 m/pixel) to generate flood detections/alerts. Based on these alerts, the Earth Observing-1 (EO-1) mission is autonomously tasked to acquire higher-resolution (10–30 m/pixel) advanced land imager data, and a number of other assets have imagery automatically requested, with yet further assets requested only in a semiautomated fashion. Based on these alerts, these data are then automatically processed to derive products such as surface water extent and volumetric water estimates in shapefile formats to enable interpretation in geographic information systems. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. To date, Terra, Aqua, EO-1, Landsat, Ikonos, WorldView-1, WorldView-2, GeoEye-1, and Radarsat-2 have been used in some fashion in the sensor web. The overall autonomous detection, tasking, data acquisition, and processing sensor web framework are described, as well as ongoing work to extend to in situ sensor networks. How the automatic triggering of targeted higher-resolution observations enables higher temporal and spatial resolution tracking of flooding events is also documented.\n
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\n\n \n \n Branch, A.; Flexas, M. M.; Claus, B.; Thompson, A. F.; Zhang, Y.; Clark, E. B.; Chien, S.; Fratantoni, D. M.; Kinsey., J. C.; Hobson, B.; Kieft, B.; and Chavez, F. P.\n\n\n \n \n \n \n \n Front Delineation and Tracking with Multiple Underwater Vehicles.\n \n \n \n \n\n\n \n\n\n\n
Journal of Field Robotics (JFR), 36(3): 568–586. 2019.\n
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@article{branch_jfr2019_front,\n\ttitle = {Front Delineation and Tracking with Multiple Underwater Vehicles},\n\tauthor = {A. Branch and M. M. Flexas and B. Claus and A. F. Thompson and Y. Zhang and E. B. Clark and S. Chien and D. M. Fratantoni and J. C. Kinsey. and B. Hobson and B. Kieft and F. P. Chavez},\n\tyear = 2019,\n\tjournal = {Journal of Field Robotics (JFR)},\n\tpublisher = {Wiley},\n\tvolume = 36,\n\tnumber = 3,\n\tpages = {568--586},\n\tdoi = {10.1002/rob.21853},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.21853},\n\tabstract = {Abstract This study describes a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles (AUVs). Multiple vehicles, equally spaced along the expected frontal boundary, complete near parallel transects orthogonal to the front. Two different techniques are used to determine the location of the front crossing from each individual vehicle transect. The first technique uses lateral gradients to detect when a change in the observed water property occurs. The second technique uses a measure of the vertical temperature structure over a single dive to detect when the vehicle is in upwelling water. Adaptive control of the vehicles ensure they remain perpendicular to the estimated front boundary as it evolves over time. This method was demonstrated in several experiment periods totaling weeks, in and around Monterey Bay, CA, in May and June of 2017. We compare the two front detection methods, a lateral gradient front detector and an upwelling front detector using the Vertical Temperature Homogeneity Index. We introduce two metrics to evaluate the adaptive control techniques presented. We show the capability of this method for repeated sampling across a dynamic ocean front using a fleet of three types of platforms: short-range Iver AUVs, Tethys-class long-range AUVs, and Seagliders. This method extends to tracking gradients of different properties using a variety of vehicles.},\n\tclearance = {CL\\#18-6807},\n\teprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/rob.21853},\n\tkeywords = {adaptive sampling, autonomous underwater vehicles, multiasset planning, ocean front tracking},\n\tproject = {keck\\_marine}\n}\n
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\n Abstract This study describes a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles (AUVs). Multiple vehicles, equally spaced along the expected frontal boundary, complete near parallel transects orthogonal to the front. Two different techniques are used to determine the location of the front crossing from each individual vehicle transect. The first technique uses lateral gradients to detect when a change in the observed water property occurs. The second technique uses a measure of the vertical temperature structure over a single dive to detect when the vehicle is in upwelling water. Adaptive control of the vehicles ensure they remain perpendicular to the estimated front boundary as it evolves over time. This method was demonstrated in several experiment periods totaling weeks, in and around Monterey Bay, CA, in May and June of 2017. We compare the two front detection methods, a lateral gradient front detector and an upwelling front detector using the Vertical Temperature Homogeneity Index. We introduce two metrics to evaluate the adaptive control techniques presented. We show the capability of this method for repeated sampling across a dynamic ocean front using a fleet of three types of platforms: short-range Iver AUVs, Tethys-class long-range AUVs, and Seagliders. This method extends to tracking gradients of different properties using a variety of vehicles.\n
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\n\n \n \n Clark, E. B.; Branch, A.; Chien, S.; Mirza, F.; Farrara, J. D.; Chao, Y.; Fratantoni, D.; Aragon, D.; Schofield, O.; Flexas, M. M.; and Thompson, A.\n\n\n \n \n \n \n \n Station-Keeping Underwater Gliders Using a Predictive Ocean Circulation Model and Applications to SWOT Calibration and Validation.\n \n \n \n \n\n\n \n\n\n\n
Journal of Oceanic Engineering (JOE). January 2019.\n
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@article{clark_joe2019_station,\n\ttitle = {Station-Keeping Underwater Gliders Using a Predictive Ocean Circulation Model and Applications to SWOT Calibration and Validation.},\n\tauthor = {E. B. Clark and A. Branch and S. Chien and F. Mirza and J. D. Farrara and Y. Chao and D. Fratantoni and D. Aragon and O. Schofield and M. M. Flexas and A. Thompson},\n\tyear = 2019,\n\tmonth = {January},\n\tjournal = {Journal of Oceanic Engineering (JOE)},\n\tdoi = {10.1109/JOE.2018.2886092},\n\turl = {https://ai.jpl.nasa.gov/public/papers/clark-joe2019-station.pdf},\n\tabstract = {Instrumented ocean moorings are the gold standard for gathering in situ measurements at a fixed location in the ocean. Because they require installation by a ship and must be secured to the seafloor, moorings are expensive, logistically difficult to deploy and maintain, and are constrained to one location once installed. To circumvent these issues, previous studies have attempted to utilize autonomous underwater gliders as platforms for virtual moorings, but these attempts have yielded comparatively large station-keeping errors due to the difficulty of glider control in dynamic ocean currents.We implemented an adaptive planner using a vehicle motion model and a predictive ocean circulation model to improve station-keeping performance by incorporating anticipated currents into glider control.We demonstrate improved station-keeping performance using our planner in both simulation and in-field deployment results, and report smaller average station-keeping error than the Monterey Bay Aquarium Research Institute's M1 mooring. Finally, we utilize our simulation framework to conduct a feasibility study on using an array of autonomous gliders as virtual moorings to conduct critical calibration and validation (CalVal) for the upcoming National Aeronautics and Space Administration, Surface Water and Ocean Topography (SWOT) Mission, instead of using permanent moorings.We show that this approach carries several advantages and has potential to meet the SWOT CalVal objectives.},\n\tclearance = {CL\\#19-1192},\n\tproject = {SWOT\\_station}\n}\n
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\n Instrumented ocean moorings are the gold standard for gathering in situ measurements at a fixed location in the ocean. Because they require installation by a ship and must be secured to the seafloor, moorings are expensive, logistically difficult to deploy and maintain, and are constrained to one location once installed. To circumvent these issues, previous studies have attempted to utilize autonomous underwater gliders as platforms for virtual moorings, but these attempts have yielded comparatively large station-keeping errors due to the difficulty of glider control in dynamic ocean currents.We implemented an adaptive planner using a vehicle motion model and a predictive ocean circulation model to improve station-keeping performance by incorporating anticipated currents into glider control.We demonstrate improved station-keeping performance using our planner in both simulation and in-field deployment results, and report smaller average station-keeping error than the Monterey Bay Aquarium Research Institute's M1 mooring. Finally, we utilize our simulation framework to conduct a feasibility study on using an array of autonomous gliders as virtual moorings to conduct critical calibration and validation (CalVal) for the upcoming National Aeronautics and Space Administration, Surface Water and Ocean Topography (SWOT) Mission, instead of using permanent moorings.We show that this approach carries several advantages and has potential to meet the SWOT CalVal objectives.\n
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\n\n \n \n Brown, D.; Huffman, W.; Sierks, H.; Thompson, D.; and Chien, S.\n\n\n \n \n \n \n Automatic detection and tracking of plumes from 67P/Churyumov-Gerasimenko in OSIRIS/Rosetta image sequences.\n \n \n \n\n\n \n\n\n\n
The Astronomical Journal (AJ), 157(1): 27. January 2019.\n
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@article{brown_aj2018_automatic,\n\ttitle = {Automatic detection and tracking of plumes from 67P/Churyumov-Gerasimenko in OSIRIS/Rosetta image sequences},\n\tauthor = {D. Brown and W. Huffman and H. Sierks and D. Thompson and S. Chien},\n\tyear = 2019,\n\tmonth = {January},\n\tjournal = {The Astronomical Journal (AJ)},\n\tvolume = 157,\n\tnumber = 1,\n\tpages = 27,\n\tabstract = {Solar system bodies such as comets and asteroids are known to eject material from their surface in the form of jets and plumes. Observations of these transient outbursts can offer insight into the inner workings and makeup of their originating body. However, the detection of and response to these events has thus far been manually controlled by ground operations, limiting the response time, due to the light time delay of ground communications. For distant bodies, the delay can exceed the duration of temporary events, making it impossible to respond with follow-up observations. To address this need, we developed a computer vision methodology for detecting plumes of the comet 67P/Churyumov–Gerasimenko from imagery acquired by the OSIRIS scientific camera system. While methods exist for the automatic detection of plumes on spherical and near-convex solar system bodies, this is the first work that addresses the case of highly irregularly shaped bodies such as 67P/Churyumov–Gerasimenko. Our work is divided into two distinct components: an image processing pipeline that refines a model-based estimate of the nucleus body, and an iterative plume detection algorithm that finds regions of local intensity maxima and joins plume segments across successively higher altitudes. Finally, we validate this method by comparing automatically labeled images to those labeled by hand, and find no significant differences in variability. This technique has utility in both ground-based analysis of plume sequences as well as onboard applications, such as isolating short sequences of high activity for priority downloading or triggering follow-up observations with additional instruments.},\n\tclearance = {CL\\#18-6921},\n\torganization = {AAS}\n}\n
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\n Solar system bodies such as comets and asteroids are known to eject material from their surface in the form of jets and plumes. Observations of these transient outbursts can offer insight into the inner workings and makeup of their originating body. However, the detection of and response to these events has thus far been manually controlled by ground operations, limiting the response time, due to the light time delay of ground communications. For distant bodies, the delay can exceed the duration of temporary events, making it impossible to respond with follow-up observations. To address this need, we developed a computer vision methodology for detecting plumes of the comet 67P/Churyumov–Gerasimenko from imagery acquired by the OSIRIS scientific camera system. While methods exist for the automatic detection of plumes on spherical and near-convex solar system bodies, this is the first work that addresses the case of highly irregularly shaped bodies such as 67P/Churyumov–Gerasimenko. Our work is divided into two distinct components: an image processing pipeline that refines a model-based estimate of the nucleus body, and an iterative plume detection algorithm that finds regions of local intensity maxima and joins plume segments across successively higher altitudes. Finally, we validate this method by comparing automatically labeled images to those labeled by hand, and find no significant differences in variability. This technique has utility in both ground-based analysis of plume sequences as well as onboard applications, such as isolating short sequences of high activity for priority downloading or triggering follow-up observations with additional instruments.\n
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\n\n \n \n Agrawal, J.; Chi, W.; Chien, S.; Rabideau, G.; Kuhn, S.; and Gaines, D.\n\n\n \n \n \n \n \n Enabling Limited Resource-Bounded Disjunction in Scheduling.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS 2019), pages 7–15, Berkeley, California, USA, July 2019. \n
Also appears at the 29th International Conference on Automated Planning and Scheduling (ICAPS) Workshop PlanRob 2019 and ICAPS SPARK 2019 and ICAPS IntEx 2019\n\n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@inproceedings{agrawal_iwpss2019_disjunction,\n\ttitle = {Enabling Limited Resource-Bounded Disjunction in Scheduling},\n\tauthor = {J. Agrawal and W. Chi and S. Chien and G. Rabideau and S. Kuhn and D. Gaines},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS 2019)},\n\taddress = {Berkeley, California, USA},\n\tpages = {7--15},\n\turl = {https://ai.jpl.nasa.gov/public/papers/agrawal-iwpss2019-disjunction.pdf},\n\tnote = {Also appears at the 29th International Conference on Automated Planning and Scheduling (ICAPS) Workshop PlanRob 2019 and ICAPS SPARK 2019 and ICAPS IntEx 2019},\n\tabstract = {We describe three approaches to enabling an extremely computationally limited embedded scheduler to consider a small number of alternative activities based on resource availability. We consider the case where the scheduler is so computationally limited that it cannot backtrack search. The first two approaches precompile resource checks (calleguards) that only enable selection of a preferred alternative activity if sufficient resources are estimated to be available to schedule the remaining activities. The final approach mimics backtracking by invoking the scheduler multiple times with the alternative activities. We present an evaluation of these techniques on mission scenarios (called sol types) from NASA's next planetary rover where these techniques are being evaluated for inclusion in an onboard scheduler.},\n\tclearance = {CL\\#19-3357},\n\tproject = {m2020\\_simple\\_planner}\n}\n
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\n We describe three approaches to enabling an extremely computationally limited embedded scheduler to consider a small number of alternative activities based on resource availability. We consider the case where the scheduler is so computationally limited that it cannot backtrack search. The first two approaches precompile resource checks (calleguards) that only enable selection of a preferred alternative activity if sufficient resources are estimated to be available to schedule the remaining activities. The final approach mimics backtracking by invoking the scheduler multiple times with the alternative activities. We present an evaluation of these techniques on mission scenarios (called sol types) from NASA's next planetary rover where these techniques are being evaluated for inclusion in an onboard scheduler.\n
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\n\n \n \n Agrawal, J.; Chi, W.; and Chien, S.\n\n\n \n \n \n \n \n Extended Abstract- Using Rescheduling and Flexible Execution to Address Uncertainty in Execution Duration for a Planetary Rover.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS 2019), pages 4–6, Berkeley, California, USA, July 2019. \n
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@inproceedings{agrawal_iwpss2019_fe,\n\ttitle = {Extended Abstract- Using Rescheduling and Flexible Execution to Address Uncertainty in Execution Duration for a Planetary Rover},\n\tauthor = {J. Agrawal and W. Chi and S. Chien},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS 2019)},\n\taddress = {Berkeley, California, USA},\n\tpages = {4--6},\n\turl = {https://ai.jpl.nasa.gov/public/papers/agrawal-iwpss2019-fe.pdf},\n\tnote = {},\n\tabstract = {The paper ``Using Rescheduling and Flexible Execution to Address Uncertainty in Execution Duration for a Planetary Rover'' [Agrawal et al. 2019] discusses several rescheduling and execution techniques to allow a scheduler to respond effectively to changes in execution, such as activities ending earlier or later than expected. We discuss these techniques both theoretically and practically in the context of limited CPU, nonzero runtime, embedded scheduler intended for NASA's next planetary rover.},\n\tclearance = {CL\\#19-2055},\n\tproject = {m2020\\_simple\\_planner}\n}\n
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\n The paper ``Using Rescheduling and Flexible Execution to Address Uncertainty in Execution Duration for a Planetary Rover'' [Agrawal et al. 2019] discusses several rescheduling and execution techniques to allow a scheduler to respond effectively to changes in execution, such as activities ending earlier or later than expected. We discuss these techniques both theoretically and practically in the context of limited CPU, nonzero runtime, embedded scheduler intended for NASA's next planetary rover.\n
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\n\n \n \n Trowbridge, M.; Shao, E.; and Knight, R.\n\n\n \n \n \n \n \n Elliptic Edge Polygons for Observational Coverage Planning.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS 2019), pages 176–184, Berkeley, CA, July 2019. \n
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@inproceedings{trowbridge_iwpss2019_eep,\n\ttitle = {Elliptic Edge Polygons for Observational Coverage Planning},\n\tauthor = {Michael Trowbridge and Elly Shao and Russell Knight},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS 2019)},\n\taddress = {Berkeley, CA},\n\tpages = {176--184},\n\turl = {https://ai.jpl.nasa.gov/public/papers/trowbridge-iwpss2019-eep.pdf},\n\tabstract = {This paper presents a representation of the polygonal footprint of an Earth-observing 2D framing sensor (i.e. instruments on Rosetta, Planet Labs SkySat) for observation coverage planning that preserves curvature of the footprint edge at little additional memory cost compared to previously published techniques. Binary operations on field-of-view, ellipsoid intersection edges are introduced, allowing them to serve as edges in a polygon. A computational experiment examines the error produced by using this method versus existing methods of camera footprint representation. Edge approximation error is most significant when the field of view footprint is large compared to the body being observed (small body exploration, fly-bys, or other distant observer scenarios), and negligible when it is small (low altitude Earth observers with narrow fields of view). Great Circles polygons are degenerate elliptic edge polygons, admitting them to the polygon and edge operations in this paper.},\n\tclearance = {CL\\#19-3145,CL\\#19-4086},\n\tproject = {EagleEye}\n}\n
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\n This paper presents a representation of the polygonal footprint of an Earth-observing 2D framing sensor (i.e. instruments on Rosetta, Planet Labs SkySat) for observation coverage planning that preserves curvature of the footprint edge at little additional memory cost compared to previously published techniques. Binary operations on field-of-view, ellipsoid intersection edges are introduced, allowing them to serve as edges in a polygon. A computational experiment examines the error produced by using this method versus existing methods of camera footprint representation. Edge approximation error is most significant when the field of view footprint is large compared to the body being observed (small body exploration, fly-bys, or other distant observer scenarios), and negligible when it is small (low altitude Earth observers with narrow fields of view). Great Circles polygons are degenerate elliptic edge polygons, admitting them to the polygon and edge operations in this paper.\n
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\n\n \n \n Russino, J. A.; Gaines, D.; Schaffer, S.; and Wong, V.\n\n\n \n \n \n \n \n Pathogen: Using Campaign Intent To Guide Onboard Planning for a Self-Reliant Rover.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS), pages 150–224, Berkeley, CA, July 2019. \n
Also appears at the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019) Workshop on Planning and Robotics (PlanRob)\n\n
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@inproceedings{russino_iwpss2019_pathogen,\n\ttitle = {Pathogen: Using Campaign Intent To Guide Onboard Planning for a Self-Reliant Rover},\n\tauthor = {Joseph A. Russino and Daniel Gaines and Steve Schaffer and Vincent Wong},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS)},\n\taddress = {Berkeley, CA},\n\tpages = {150--224},\n\turl = {https://ai.jpl.nasa.gov/public/papers/russino-iwpss2019-pathogen.pdf},\n\tnote = {Also appears at the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019) Workshop on Planning and Robotics (PlanRob)},\n\tabstract = {Exploring subsurface structures with autonomous robots is of growing interest in the context of planetary caves studies. Communication in these environments can change rapidly as assets move around, which can complicate coordination among multiple assets. Limited lifetime must also be accounted for when exploring these subsurface structures, because it is likely that recharging the batteries of the robots will not be possible. The combination of uncertain communication and limited mission duration suggests that accounting for energy when transmitting data out of cave-like structures would be beneficial to mission success. Therefore, in this paper we investigate different energy-aware data routing strategies for multi-robot scenarios where asset lifetime is limited and benchmark their performance in a simulation environment},\n\tclearance = {CL\\#19-1852},\n\tproject = {srr}\n}\n
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\n Exploring subsurface structures with autonomous robots is of growing interest in the context of planetary caves studies. Communication in these environments can change rapidly as assets move around, which can complicate coordination among multiple assets. Limited lifetime must also be accounted for when exploring these subsurface structures, because it is likely that recharging the batteries of the robots will not be possible. The combination of uncertain communication and limited mission duration suggests that accounting for energy when transmitting data out of cave-like structures would be beneficial to mission success. Therefore, in this paper we investigate different energy-aware data routing strategies for multi-robot scenarios where asset lifetime is limited and benchmark their performance in a simulation environment\n
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\n\n \n \n Troesch, M.; Mirza, F.; Rabideau, G.; and Chien, S.\n\n\n \n \n \n \n \n Onboard re-planning for robust mapping using pre-compiled backup observations.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS), pages 168–175, Berkeley, California, USA, July 2019. \n
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@inproceedings{troesch_iwpss2019_robustmapping,\n\ttitle = {Onboard re-planning for robust mapping using pre-compiled backup observations},\n\tauthor = {M. Troesch and F. Mirza and G. Rabideau and S. Chien},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS)},\n\taddress = {Berkeley, California, USA},\n\tpages = {168--175},\n\turl = {https://ai.jpl.nasa.gov/public/papers/troesch-iwpss2019-robustmapping.pdf},\n\tabstract = {Mapping target bodies by imaging as much of the surface as possible is a common scientific goal for space missions where a spacecraft is orbiting a body, such as a comet, asteroid, or planet. An observation schedule to achieve the mapping goal is generally generated on the ground and then uploaded to the spacecraft. However, without some re-planning capa- bility onboard, opportunities may be lost due to observation failures or unexpected changes in resource availability. The computational and memory restrictions for spacecraft make it difficult to perform the geometric reasoning and calculations required to select observations to achieve the mapping goal onboard, meaning that any re-planning capabilities are also limited. In this paper we present a method for robust map- ping by re-planning observations onboard using pre-compiled backup observations. The nominal schedule and backup ob- servations are generated using the Compressed Large-scale Activity Scheduler and Planner, which are then translated into a Task Network and goal definitions. These can be used by MEXEC, an onboard planning and execution software. We demonstrate our method using a hypothetical scenario of a spacecraft orbiting a comet.},\n\tclearance = {CL\\#19-3316},\n\tproject = {mexec, clasp}\n}\n
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\n Mapping target bodies by imaging as much of the surface as possible is a common scientific goal for space missions where a spacecraft is orbiting a body, such as a comet, asteroid, or planet. An observation schedule to achieve the mapping goal is generally generated on the ground and then uploaded to the spacecraft. However, without some re-planning capa- bility onboard, opportunities may be lost due to observation failures or unexpected changes in resource availability. The computational and memory restrictions for spacecraft make it difficult to perform the geometric reasoning and calculations required to select observations to achieve the mapping goal onboard, meaning that any re-planning capabilities are also limited. In this paper we present a method for robust map- ping by re-planning observations onboard using pre-compiled backup observations. The nominal schedule and backup ob- servations are generated using the Compressed Large-scale Activity Scheduler and Planner, which are then translated into a Task Network and goal definitions. These can be used by MEXEC, an onboard planning and execution software. We demonstrate our method using a hypothetical scenario of a spacecraft orbiting a comet.\n
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\n\n \n \n Johnston, M. D.\n\n\n \n \n \n \n \n User Preference Optimization for Oversubscribed Scheduling of NASA's Deep Space Network.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS), pages 86–92, Berkeley, California, USA, July 2019. \n
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@inproceedings{johnston_iwpss2019_userprefopt,\n\ttitle = {User Preference Optimization for Oversubscribed Scheduling of NASA's Deep Space Network},\n\tauthor = {Mark D. Johnston},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS)},\n\taddress = {Berkeley, California, USA},\n\tpages = {86--92},\n\turl = {https://ai.jpl.nasa.gov/public/papers/johnston-iwpss2019-userprefopt.pdf},\n\tabstract = {NASA's Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. With three complexes spread roughly evenly around the globe, the DSN provides services to dozens of active missions. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and projected demand has exceeded network capacity for quite some time. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. The delays inherent in this process are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40\\% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static priority list to address a similar problem: missions are ranked in priority order, and the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper reports on a new paradigm for DSN scheduling that addresses the key problems inherent in the current process. The main characteristics of the new approach are to use loading-based limits on requested time, and user preferences as the basis for optimization criteria.},\n\tclearance = {CL\\#19-3416},\n\tproject = {SSS}\n}\n
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\n NASA's Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. With three complexes spread roughly evenly around the globe, the DSN provides services to dozens of active missions. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and projected demand has exceeded network capacity for quite some time. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. The delays inherent in this process are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static priority list to address a similar problem: missions are ranked in priority order, and the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper reports on a new paradigm for DSN scheduling that addresses the key problems inherent in the current process. The main characteristics of the new approach are to use loading-based limits on requested time, and user preferences as the basis for optimization criteria.\n
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\n\n \n \n Vaquero, T.; Troesch, M.; Net, M. S.; Gao, J.; and Chien, S.\n\n\n \n \n \n \n \n Energy-Aware Data Routing for Disruption Tolerant Networks in Planetary Cave Exploration.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS), pages 186–193, Berkeley, CA, July 2019. \n
Also appears at the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019) Workshop on Planning and Robotics (PlanRob)\n\n
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@inproceedings{vaquero_et_al_iwpss2019_routing,\n\ttitle = {Energy-Aware Data Routing for Disruption Tolerant Networks in Planetary Cave Exploration},\n\tauthor = {Tiago Vaquero and Martina Troesch and Marc Sanchez Net and Jay Gao and Steve Chien},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS)},\n\taddress = {Berkeley, CA},\n\tpages = {186--193},\n\turl = {https://ai.jpl.nasa.gov/public/papers/vaquero-et-al-iwpss2019-routing.pdf},\n\tnote = {Also appears at the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019) Workshop on Planning and Robotics (PlanRob)},\n\tabstract = {Exploring subsurface structures with autonomous robots is of growing interest in the context of planetary caves studies. Communication in these environments can change rapidly as assets move around, which can complicate coordination among multiple assets. Limited lifetime must also be accounted for when exploring these subsurface structures, because it is likely that recharging the batteries of the robots will not be possible. The combination of uncertain communication and limited mission duration suggests that accounting for energy when transmitting data out of cave-like structures would be beneficial to mission success. Therefore, in this paper we investigate different energy-aware data routing strategies for multi-robot scenarios where asset lifetime is limited and benchmark their performance in a simulation environment.},\n\tclearance = {CL\\#19-3239},\n\tproject = {CaveRovers}\n}\n
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\n Exploring subsurface structures with autonomous robots is of growing interest in the context of planetary caves studies. Communication in these environments can change rapidly as assets move around, which can complicate coordination among multiple assets. Limited lifetime must also be accounted for when exploring these subsurface structures, because it is likely that recharging the batteries of the robots will not be possible. The combination of uncertain communication and limited mission duration suggests that accounting for energy when transmitting data out of cave-like structures would be beneficial to mission success. Therefore, in this paper we investigate different energy-aware data routing strategies for multi-robot scenarios where asset lifetime is limited and benchmark their performance in a simulation environment.\n
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\n\n \n \n Hackett, T.; Bilen, S.; and Johnston, M. D.\n\n\n \n \n \n \n \n Investigating a Demand Access Scheduling Paradigm for NASA's Deep Space Network.\n \n \n \n \n\n\n \n\n\n\n In
11th International Workshop on Planning and Scheduling for Space (IWPSS), pages 51–60, Berkeley, California, USA, July 2019. \n
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@inproceedings{hackett_iwpss2019_demandaccess,\n\ttitle = {Investigating a Demand Access Scheduling Paradigm for NASA's Deep Space Network},\n\tauthor = {Timothy Hackett and Sven Bilen and Mark D. Johnston},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {11th International Workshop on Planning and Scheduling for Space (IWPSS)},\n\taddress = {Berkeley, California, USA},\n\tpages = {51--60},\n\turl = {https://ai.jpl.nasa.gov/public/papers/hackett-iwpss2019-demandaccess.pdf},\n\tabstract = {NASA's Deep Space Network supports the communications to and from spacecraft, rovers, and landers across our solar system and beyond. The weekly tracking requirements for these spacecraft are scheduled by mission representatives at least eight weeks before the start of the track through a combination of automated algorithms and peer-to-peer negotiations. This process has worked well for traditional users with deterministic science collections, such as those doing mapping and imaging. But, this process will not scale well to accommodate a new class of users whose data collections are not completely predictable (i.e., event-driven science), which includes both traditional, deterministic users with unexpected discoveries as well as autonomous users exploring and monitoring for certain events, such as solar flares. In this paper, we propose a ``demand access'' scheduling approach in which the spacecraft, rovers, and landers themselves request track time on the network using a beacon-tone system and are scheduled track time ``on-the-fly'' using pre-scheduled shared-user block tracks. We show through simulation that this demand-access approach can both decrease the mean duration between the time of data collection to the start of the downlink and the number of tracks required compared to the traditional scheduling method for an example mission concept of autonomous SmallSat explorers at near-Earth asteroids. We also show how this demand-access approach can be used in combination with the traditional scheduling method to support legacy users.},\n\tproject = {SSS}\n}\n
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\n NASA's Deep Space Network supports the communications to and from spacecraft, rovers, and landers across our solar system and beyond. The weekly tracking requirements for these spacecraft are scheduled by mission representatives at least eight weeks before the start of the track through a combination of automated algorithms and peer-to-peer negotiations. This process has worked well for traditional users with deterministic science collections, such as those doing mapping and imaging. But, this process will not scale well to accommodate a new class of users whose data collections are not completely predictable (i.e., event-driven science), which includes both traditional, deterministic users with unexpected discoveries as well as autonomous users exploring and monitoring for certain events, such as solar flares. In this paper, we propose a ``demand access'' scheduling approach in which the spacecraft, rovers, and landers themselves request track time on the network using a beacon-tone system and are scheduled track time ``on-the-fly'' using pre-scheduled shared-user block tracks. We show through simulation that this demand-access approach can both decrease the mean duration between the time of data collection to the start of the downlink and the number of tracks required compared to the traditional scheduling method for an example mission concept of autonomous SmallSat explorers at near-Earth asteroids. We also show how this demand-access approach can be used in combination with the traditional scheduling method to support legacy users.\n
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\n\n \n \n Fesq, L.; Beauchamp, P.; Donner, A.; Bocchino, R.; Kennedy, B.; Mirza, F.; Mohan, S.; Sternberg, D.; Smith, M. W; Troesch, M.; and others\n\n\n \n \n \n \n \n Extended mission technology demonstrations using the ASTERIA spacecraft.\n \n \n \n \n\n\n \n\n\n\n In
2019 IEEE Aerospace Conference, 2019. IEEE\n
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@inproceedings{fesq_asteria_iee-aero_2019,\n\ttitle = {Extended mission technology demonstrations using the ASTERIA spacecraft},\n\tauthor = {Fesq, Lorraine and Beauchamp, Patricia and Donner, Amanda and Bocchino, Rob and Kennedy, Brian and Mirza, Faiz and Mohan, Swati and Sternberg, David and Smith, Matthew W and Troesch, Martina and others},\n\tyear = 2019,\n\tbooktitle = {2019 IEEE Aerospace Conference},\n\turl = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\\&arnumber=8742020},\n\torganization = {IEEE},\n\tproject = {asteria}\n}\n
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\n\n \n \n Vaquero, T. S.; Chien, S.; Agrawal, J.; Chi, W.; and Huntsberger, T.\n\n\n \n \n \n \n \n Temporal Brittleness Analysis of Task Networks for Planetary Rovers.\n \n \n \n \n\n\n \n\n\n\n In
29th International Conference on Automated Planning and Scheduling (ICAPS), pages 564–572, Berkeley, CA, July 2019. \n
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@inproceedings{vaquero_chien_et_al_icaps19_brittleness,\n\ttitle = {Temporal Brittleness Analysis of Task Networks for Planetary Rovers},\n\tauthor = {Tiago Stegun Vaquero and Steve Chien and Jagriti Agrawal and Wayne Chi and Terrance Huntsberger},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {29th International Conference on Automated Planning and Scheduling (ICAPS)},\n\taddress = {Berkeley, CA},\n\tpages = {564--572},\n\turl = {https://ai.jpl.nasa.gov/public/papers/vaquero-chien-et-al-icaps2019-brittleness.pdf},\n\tabstract = {We propose a new method to analyze the temporal brittleness of task networks, which allows the detection and enumeration of activities that, with modest task execution duration variation make the execution of the task network dynamically uncontrollable. In this method, we introduce a metric for measuring an activity brittleness - defined as the degree of acceptable deviation of its nominal duration - and describe how that measurement is mapped to task network structure. Complementary to existing work on plan robustness analysis which informs how likely a task network is to succeed or not, the proposed analysis and metric go deeper to pinpoint the sources of potential brittleness due to temporal constraints and to focus either human designers and/or automated task network generators (e.g. scheduler/planners) to address sources of undesirable brittleness. We apply the approach to a set of task networks (called sol types) in development for NASA's next planetary rover and present common patterns that are sources of brittleness. These techniques are currently under evaluation for potential use supporting operations of the Mars 2020 rover.},\n\tclearance = {CL\\#19-1620},\n\tproject = {m2020, Brittleness}\n}\n
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\n We propose a new method to analyze the temporal brittleness of task networks, which allows the detection and enumeration of activities that, with modest task execution duration variation make the execution of the task network dynamically uncontrollable. In this method, we introduce a metric for measuring an activity brittleness - defined as the degree of acceptable deviation of its nominal duration - and describe how that measurement is mapped to task network structure. Complementary to existing work on plan robustness analysis which informs how likely a task network is to succeed or not, the proposed analysis and metric go deeper to pinpoint the sources of potential brittleness due to temporal constraints and to focus either human designers and/or automated task network generators (e.g. scheduler/planners) to address sources of undesirable brittleness. We apply the approach to a set of task networks (called sol types) in development for NASA's next planetary rover and present common patterns that are sources of brittleness. These techniques are currently under evaluation for potential use supporting operations of the Mars 2020 rover.\n
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\n\n \n \n Yelamanchili, A.; Moy, A.; Chien, S.; Eldering, A.; Pavlick, R.; and Wells, C.\n\n\n \n \n \n \n \n Automated Policy-based Scheduling for the OCO-3 mission.\n \n \n \n \n\n\n \n\n\n\n In
Earth Science Technology Forum (ESTF 2019), Moffett Field, California, USA, June 2019. \n
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@inproceedings{chien_estf2019_oco3,\n\ttitle = {Automated Policy-based Scheduling for the OCO-3 mission},\n\tauthor = {A. Yelamanchili and A. Moy and S. Chien and A. Eldering and R. Pavlick and C. Wells},\n\tyear = 2019,\n\tmonth = {June},\n\tbooktitle = {Earth Science Technology Forum (ESTF 2019)},\n\taddress = {Moffett Field, California, USA},\n\turl = {https://ai.jpl.nasa.gov/public/posters/chien-estf2019-oco3.pdf},\n\tnote = {},\n\tabstract = {Automated scheduling is being deployed for operations of the Orbiting Carbon Observatory-3 (OCO-3). The OCO-3 scheduling process begins with a mostly-automated dynamic science priority assignment that is input to an automated scheduling of area targets, calibration targets, nadir, and glint mode. We describe the priority first area scheduling algorithm as well as use of AI scheduling for instrument callibration operations. Finally we describe fine pointing scheduling techniques relevant to OCO-3 and other missions but not baselined for OCO-3 usage.},\n\tclearance = {CL\\#19-3106},\n\tproject = {oco3, clasp}\n}\n
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\n Automated scheduling is being deployed for operations of the Orbiting Carbon Observatory-3 (OCO-3). The OCO-3 scheduling process begins with a mostly-automated dynamic science priority assignment that is input to an automated scheduling of area targets, calibration targets, nadir, and glint mode. We describe the priority first area scheduling algorithm as well as use of AI scheduling for instrument callibration operations. Finally we describe fine pointing scheduling techniques relevant to OCO-3 and other missions but not baselined for OCO-3 usage.\n
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\n\n \n \n Yelamanchili, A.; Chien, S.; Moy, A.; Cawse-Nicholson, K.; Padams, J.; and Freeborn, D.\n\n\n \n \n \n \n \n Automated Policy-based Scheduling for the ECOSTRESS mission.\n \n \n \n \n\n\n \n\n\n\n In
Earth Science Technology Forum (ESTF 2019), Moffett Field, California, USA, June 2019. \n
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@inproceedings{chien_estf2019_ecostress,\n\ttitle = {Automated Policy-based Scheduling for the ECOSTRESS mission},\n\tauthor = {A. Yelamanchili and S. Chien and A. Moy and K. Cawse-Nicholson and J. Padams and D. Freeborn},\n\tyear = 2019,\n\tmonth = {June},\n\tbooktitle = {Earth Science Technology Forum (ESTF 2019)},\n\taddress = {Moffett Field, California, USA},\n\turl = {https://ai.jpl.nasa.gov/public/posters/chien-estf2019-ecostress.pdf},\n\tnote = {},\n\tabstract = {Automated scheduling is being used for operations of the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). Coverage planning technology in the CLASP scheduler was used to: evaluate designs of the overall science campaign implementation prior to launch, nominal operations , and has been key in the ability to design new science coverage strategies and even updated scheduling approaches to address hardware challenges on orbit. In particular we describe: rapid assessment of operations strategies to address radiation sensitivity encountered during operations, automated scheduling of Mass Storage Unit ring buffer resets to address hardware issues encountered in flight, scheduler handling of along track orbit uncertainty, and updated mass storage -less operations schemes.},\n\tclearance = {CL\\#19-3109},\n\tproject = {ecostress, clasp}\n}\n
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\n Automated scheduling is being used for operations of the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). Coverage planning technology in the CLASP scheduler was used to: evaluate designs of the overall science campaign implementation prior to launch, nominal operations , and has been key in the ability to design new science coverage strategies and even updated scheduling approaches to address hardware challenges on orbit. In particular we describe: rapid assessment of operations strategies to address radiation sensitivity encountered during operations, automated scheduling of Mass Storage Unit ring buffer resets to address hardware issues encountered in flight, scheduler handling of along track orbit uncertainty, and updated mass storage -less operations schemes.\n
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\n\n \n \n Yelamanchili, A.; Chien, S.; J.Russino; Wells, C.; Green, R.; Oaida, B.; and Thompson, D. R.\n\n\n \n \n \n \n \n Mission Analysis for EMIT using Automated Coverage Scheduling.\n \n \n \n \n\n\n \n\n\n\n In
Earth Science Technology Forum (ESTF 2019), Moffett Field, California, USA, June 2019. \n
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@inproceedings{chien_estf2019_emit,\n\ttitle = {Mission Analysis for EMIT using Automated Coverage Scheduling},\n\tauthor = {A. Yelamanchili and S. Chien and J.Russino and C. Wells and R. Green and B. Oaida and D. R. Thompson},\n\tyear = 2019,\n\tmonth = {June},\n\tbooktitle = {Earth Science Technology Forum (ESTF 2019)},\n\taddress = {Moffett Field, California, USA},\n\turl = {https://ai.jpl.nasa.gov/public/posters/chien-estf2019-emit.pdf},\n\tnote = {},\n\tabstract = {Automated scheduling technology is being used to analyze trades between differing instrument designs and observation campaign strategies for the Earth Surface Mineral Dust Source Investigation (EMIT) mission. Automated coverage scheduling can be applied to a range of mission scenarios (a) hardware configurations (e.g. pointing, SSR sizing); (b) observation design (e.g. geometric constraints such as look angle, illumination); (c) observation coverage strategy; and (d) definition of areal targets and specific coverage criteria (grid resolution, percentage coverage).},\n\tclearance = {CL\\#19-3107},\n\tproject = {emit, clasp}\n}\n
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\n Automated scheduling technology is being used to analyze trades between differing instrument designs and observation campaign strategies for the Earth Surface Mineral Dust Source Investigation (EMIT) mission. Automated coverage scheduling can be applied to a range of mission scenarios (a) hardware configurations (e.g. pointing, SSR sizing); (b) observation design (e.g. geometric constraints such as look angle, illumination); (c) observation coverage strategy; and (d) definition of areal targets and specific coverage criteria (grid resolution, percentage coverage).\n
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\n\n \n \n Chien, S.; Yelamanchili, A.; and Doubleday, J.\n\n\n \n \n \n \n \n Policy-based automated science coverage scheduling for earth science mission analysis and operations (NISAR, ECOSTRESS, OCO-3, and EMIT).\n \n \n \n \n\n\n \n\n\n\n In
Earth Science Technology Forum (ESTF 2019), Moffett Field, California, USA, June 2019. \n
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@inproceedings{chien_estf2019_overview,\n\ttitle = {Policy-based automated science coverage scheduling for earth science mission analysis and operations (NISAR, ECOSTRESS, OCO-3, and EMIT)},\n\tauthor = {S. Chien and A. Yelamanchili and J. Doubleday},\n\tyear = 2019,\n\tmonth = {June},\n\tbooktitle = {Earth Science Technology Forum (ESTF 2019)},\n\taddress = {Moffett Field, California, USA},\n\turl = {https://ai.jpl.nasa.gov/public/presentations/chien-estf2019-overview.pdf},\n\tnote = {},\n\tabstract = {Automated policy based coverage scheduling is in operational usage in both mission analysis and mission operations for a range of Earth Science missions. We present an overview of the coverage analysis and search-based automated scheduling techniques. Then we describe some of the challenges in modeling complex mission constraints and unique aspects of some of the target missions, drawing examples from work for the NISAR, ECOSTRESS, OCO-3, and EMIT missions. Finally, we describe some promising real for future work including increasing parallelism and leveraging recent advances in hardware for geometric computation.},\n\tclearance = {CL\\#19-2980},\n\tproject = {nisar, ecostress, oco-3, emit, clasp}\n}\n
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\n Automated policy based coverage scheduling is in operational usage in both mission analysis and mission operations for a range of Earth Science missions. We present an overview of the coverage analysis and search-based automated scheduling techniques. Then we describe some of the challenges in modeling complex mission constraints and unique aspects of some of the target missions, drawing examples from work for the NISAR, ECOSTRESS, OCO-3, and EMIT missions. Finally, we describe some promising real for future work including increasing parallelism and leveraging recent advances in hardware for geometric computation.\n
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\n\n \n \n Chi, W.; Agrawal, J.; Chien, S.; Fosse, E.; and Guduri, U.\n\n\n \n \n \n \n \n Optimizing Parameters for Uncertain Execution and Rescheduling Robustness.\n \n \n \n \n\n\n \n\n\n\n In
International Conference on Automated Planning and Scheduling (ICAPS 2019), Berkeley, California, USA, July 2019. \n
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@inproceedings{chi_icaps2019_optimizing,\n\ttitle = {Optimizing Parameters for Uncertain Execution and Rescheduling Robustness},\n\tauthor = {W. Chi and J. Agrawal and S. Chien and E. Fosse and U. Guduri},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {International Conference on Automated Planning and Scheduling (ICAPS 2019)},\n\taddress = {Berkeley, California, USA},\n\turl = {https://ai.jpl.nasa.gov/public/papers/chi-icaps2019-optimizing.pdf},\n\tabstract = {We describe use of Monte Carlo simulation to optimize schedule parameters for execution and rescheduling robustness in the face of execution uncertainties. We search in the activity input parameter space where a) the onboard scheduler is a one shot non-backtracking scheduler and b) the activity input priority determines the order in which activities are considered for placement in the schedule. We show that simulation driven search for activity parameters outperforms static priority assignment. Our approach can be viewed as using simulation feedback to determine problem specific heuristics e.g. Squeaky Wheel Optimization. These techniques are currently baselined for use in the ground operations of NASA's next planetary rover, the Mars 2020 rover.},\n\tclearance = {CL\\#19-1686},\n\tproject = {m2020\\_simple\\_planner}\n}\n
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\n We describe use of Monte Carlo simulation to optimize schedule parameters for execution and rescheduling robustness in the face of execution uncertainties. We search in the activity input parameter space where a) the onboard scheduler is a one shot non-backtracking scheduler and b) the activity input priority determines the order in which activities are considered for placement in the schedule. We show that simulation driven search for activity parameters outperforms static priority assignment. Our approach can be viewed as using simulation feedback to determine problem specific heuristics e.g. Squeaky Wheel Optimization. These techniques are currently baselined for use in the ground operations of NASA's next planetary rover, the Mars 2020 rover.\n
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\n\n \n \n Moy, A.; Yelamanchili, A.; Chien, S.; Eldering, A.; and Pavlick, R.\n\n\n \n \n \n \n \n Automated Scheduling for the OCO-3 Mission.\n \n \n \n \n\n\n \n\n\n\n In
International Workshop for Planning and Scheduling for Space (IWPSS 2019), pages 195–203, Berkeley, California, USA, July 2019. \n
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@inproceedings{yelamanchili_iwpss2019_oco3,\n\ttitle = {Automated Scheduling for the OCO-3 Mission},\n\tauthor = {A. Moy and A. Yelamanchili and S. Chien and A. Eldering and R. Pavlick},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {International Workshop for Planning and Scheduling for Space (IWPSS 2019)},\n\taddress = {Berkeley, California, USA},\n\tpages = {195--203},\n\turl = {https://ai.jpl.nasa.gov/public/papers/yelamanchili-iwpss2019-oco3-scheduling.pdf},\n\tabstract = {We describe the automated scheduling system in development and in use for the Orbiting Carbon Observatory-3 Mission (OCO-3), which launched to the International Space Station in May 2019. We first describe the high level scheduling prob- lem of scheduling the four types of observations: nadir, glint, target, and snapshot area map. We then describe the major complexity of OCO-3 scheduling - enforcing geometric visi- bility constraints for snapshot area map and target modes. We also describe an automated scheduling of instrument pointing calibration. We then describe current and related work as well as future directions for the scheduling of OCO-3.},\n\tclearance = {CL\\#19-3425},\n\tproject = {oco3, clasp}\n}\n
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\n We describe the automated scheduling system in development and in use for the Orbiting Carbon Observatory-3 Mission (OCO-3), which launched to the International Space Station in May 2019. We first describe the high level scheduling prob- lem of scheduling the four types of observations: nadir, glint, target, and snapshot area map. We then describe the major complexity of OCO-3 scheduling - enforcing geometric visi- bility constraints for snapshot area map and target modes. We also describe an automated scheduling of instrument pointing calibration. We then describe current and related work as well as future directions for the scheduling of OCO-3.\n
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\n\n \n \n Yelamanchili, A.; Chien, S.; Moy, A.; Shao, E.; Trowbridge, M.; Cawse-Nicholson, K.; Padams, J.; and Freeborn, D.\n\n\n \n \n \n \n \n Automated Science Scheduling for the ECOSTRESS Mission.\n \n \n \n \n\n\n \n\n\n\n In
International Workshop for Planning and Scheduling for Space (IWPSS 2019), pages 204–211, Berkeley, California, USA, July 2019. \n
Also appears at ICAPS SPARK 2019\n\n
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@inproceedings{yelamanchili_iwpss2019_ecostress,\n\ttitle = {Automated Science Scheduling for the ECOSTRESS Mission},\n\tauthor = {A. Yelamanchili and S. Chien and A. Moy and E. Shao and M. Trowbridge and K. Cawse-Nicholson and J. Padams and D. Freeborn},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {International Workshop for Planning and Scheduling for Space (IWPSS 2019)},\n\taddress = {Berkeley, California, USA},\n\tpages = {204--211},\n\turl = {https://ai.jpl.nasa.gov/public/papers/yelamanchili-iwpss2019-ecostress-scheduling.pdf},\n\tnote = {Also appears at ICAPS SPARK 2019},\n\tabstract = {We describe the use of an automated scheduling system for observation policy design and to schedule operations of the NASA (National Aeronautics and Space Administration) ECOSystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). We describe the adaptation of the Compressed Large-scale Activity Scheduler and Planner (CLASP) scheduling system to the ECOSTRESS schedul- ing problem, highlighting multiple use cases for automated scheduling and several challenges for the scheduling technol- ogy: handling long-term campaigns with changing informa- tion, Mass Storage Unit Ring Buffer operations challenges, and orbit uncertainty. The described scheduling system has been used for operations of the ECOSTRESS instrument since its nominal operations start July 2018 and is expected to operate until mission end in Summer 2019.},\n\tclearance = {CL\\#19-3340},\n\tproject = {ecostress, clasp}\n}\n
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\n We describe the use of an automated scheduling system for observation policy design and to schedule operations of the NASA (National Aeronautics and Space Administration) ECOSystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). We describe the adaptation of the Compressed Large-scale Activity Scheduler and Planner (CLASP) scheduling system to the ECOSTRESS schedul- ing problem, highlighting multiple use cases for automated scheduling and several challenges for the scheduling technol- ogy: handling long-term campaigns with changing informa- tion, Mass Storage Unit Ring Buffer operations challenges, and orbit uncertainty. The described scheduling system has been used for operations of the ECOSTRESS instrument since its nominal operations start July 2018 and is expected to operate until mission end in Summer 2019.\n
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\n\n \n \n Chi, W.; Chien, S.; and Agrawal, J.\n\n\n \n \n \n \n \n Scheduling with Complex Consumptive resources for a Planetary Rover.\n \n \n \n \n\n\n \n\n\n\n In
International Workshop for Planning and Scheduling for Space (IWPSS 2019), pages 25–33, Berkeley, California, USA, July 2019. \n
Also appears at ICAPS PlanRob 2019 and ICAPS SPARK 2019\n\n
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@inproceedings{chi_icaps2019_scheduling,\n\ttitle = {Scheduling with Complex Consumptive resources for a Planetary Rover},\n\tauthor = {W. Chi and S. Chien and J. Agrawal},\n\tyear = 2019,\n\tmonth = {July},\n\tbooktitle = {International Workshop for Planning and Scheduling for Space (IWPSS 2019)},\n\taddress = {Berkeley, California, USA},\n\tpages = {25--33},\n\turl = {https://ai.jpl.nasa.gov/public/papers/chi-icaps2019-scheduling.pdf},\n\tnote = {Also appears at ICAPS PlanRob 2019 and ICAPS SPARK 2019},\n\tabstract = {Generating and scheduling activities is particularly challenging when considering both consumptive resources and complex resource interactions such as time-dependent resource usage. We present three methods of determining valid temporal placement intervals for an activity in a temporally grounded plan in the presence of such constraints. We introduce the Max Duration and Probe algorithms which are sound, but incomplete, and the Linear algorithm which is sound and complete for linear rate resource consumption. We apply these techniques to the problem of scheduling for a planetary rover where the awake durations are affected by existing activities. We demonstrate how the Probe algorithm performs competitively with the Linear algorithm given an advantageous problem space and well-defined heuristics. We show that the Probe and Linear algorithms outperform the Max Duration algorithm empirically. We then empirically present the runtime differences between the three algorithms. The Probe algorithm is currently baselined for use in the onboard scheduler for NASA's next planetary rover, the Mars 2020 rover.},\n\tclearance = {CL\\#19-3545},\n\tproject = {m2020\\_simple\\_planner}\n}\n
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\n Generating and scheduling activities is particularly challenging when considering both consumptive resources and complex resource interactions such as time-dependent resource usage. We present three methods of determining valid temporal placement intervals for an activity in a temporally grounded plan in the presence of such constraints. We introduce the Max Duration and Probe algorithms which are sound, but incomplete, and the Linear algorithm which is sound and complete for linear rate resource consumption. We apply these techniques to the problem of scheduling for a planetary rover where the awake durations are affected by existing activities. We demonstrate how the Probe algorithm performs competitively with the Linear algorithm given an advantageous problem space and well-defined heuristics. We show that the Probe and Linear algorithms outperform the Max Duration algorithm empirically. We then empirically present the runtime differences between the three algorithms. The Probe algorithm is currently baselined for use in the onboard scheduler for NASA's next planetary rover, the Mars 2020 rover.\n
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\n\n \n \n Ramaswamy, B. A.; Agrawal, J.; Chi, W.; Kim, S. Y.; Davidoff, S.; and Chien, S.\n\n\n \n \n \n \n \n Supporting Automation in Spacecraft Activity Planning with Simulation and Visualization.\n \n \n \n \n\n\n \n\n\n\n In
Proceedings of Science and Technology Forum and Exposition, 2019. AIAA\n
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@inproceedings{basak_aiaa2019_supporting,\n\ttitle = {Supporting Automation in Spacecraft Activity Planning with Simulation and Visualization},\n\tauthor = {Basak Alper Ramaswamy and Jagriti Agrawal and Wayne Chi and So Young Kim and Scott Davidoff and Steve Chien},\n\tyear = 2019,\n\tbooktitle = {Proceedings of Science and Technology Forum and Exposition},\n\turl = {https://ai.jpl.nasa.gov/public/papers/basak-aiaa2019-supporting.pdf},\n\tabstract = {Automation is gaining momentum in spacecraft operations, however, at a much slower pace than comparable application domains. The reasons behind slow adoption is (1) the need for high reliability and (2) the limited interaction between human operators and the automated systems. For automated systems to be adopted and trusted by humans, humans need to gain intuition about the decision making process of the automated system and trust in its execution \\cite{lee2004trust}. In this paper, we present how simulation and visualization can enhance adoption of an automated on-board activity scheduling system, specifically in the context of Mars2020 rover mission \\cite{chi2018embedding}. The visualization aims to communicate to the users degree of variance and uncertainty in possible schedule execution. Our preliminary validation results suggest that the proposed visualization increases operators' confidence in---and likelihood of adopting---the automated scheduling system.},\n\tclearance = {CL\\#18-7364},\n\torganization = {AIAA},\n\tproject = {m2020}\n}\n
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\n Automation is gaining momentum in spacecraft operations, however, at a much slower pace than comparable application domains. The reasons behind slow adoption is (1) the need for high reliability and (2) the limited interaction between human operators and the automated systems. For automated systems to be adopted and trusted by humans, humans need to gain intuition about the decision making process of the automated system and trust in its execution i̧telee2004trust. In this paper, we present how simulation and visualization can enhance adoption of an automated on-board activity scheduling system, specifically in the context of Mars2020 rover mission i̧techi2018embedding. The visualization aims to communicate to the users degree of variance and uncertainty in possible schedule execution. Our preliminary validation results suggest that the proposed visualization increases operators' confidence in—and likelihood of adopting—the automated scheduling system.\n
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