@inproceedings{wolf-rahmani-croix-et-al-2017,
  author = {Michael T. Wolf and Amir Rahmani and Jean-Pierre de la Croix and Gail Woodward and Vander Hook, Joshua and David Brown and Steve Schaffer and Christopher Lim and Philip Bailey and Scott Tepsuporn and Marc Pomerantz and Viet Nguyen and Cristina Sorice and Michael Sandoval},
  title = {CARACaS Multi-Agent Maritime Autonomy for Unmanned Surface Vehicles in the Swarm II Harbor Patrol Demonstration},
  booktitle = {SPIE 10195},
  year = {2017},
  month = {April},
  doi = {10.1117/12.2262067},
  address = {Anaheim, CA},
  url = {http://dx.doi.org/10.1117/12.2262067},
  clearance = {CL#17-1581},
}

@article{francis-estlin-doran-et-al-2017,
  author = {R. Francis and T. Estlin and G. Doran and S. Johnstone and D. Gaines and V. Verma and M. Burl and J. Frydenvang and S. Montaño and R. C. Wiens and S. Schaffer and O. Gasnault and L. DeFlores and D. Blaney and B. Bornstein},
  title = {AEGIS Autonomous Targeting for ChemCam on Mars Science Laboratory: Deployment and Results of Initial Science Team Use},
  journal = {Science Robotics},
  year = {2017},
  month = {June},
  abstract = {Limitations on interplanetary communications create operations latencies and slow progress in planetary surface missions, with particular challenges to narrow-field-of-view science instruments requiring precise targeting. The AEGIS (Autonomous Exploration for Gathering Increased Science) autonomous targeting system has been in routine use on NASA's Curiosity Mars rover since May 2016, selecting targets for the ChemCam remote geochemical spectrometer instrument. AEGIS operates in two modes; in autonomous target selection, it identifies geological targets in images from the rover's navigation cameras, choosing for itself targets that match the parameters specified by mission scientists the most, and immediately measures them with ChemCam, without Earth in the loop. In autonomous pointing refinement, the system corrects small pointing errors on the order of a few milliradians in observations targeted by operators on Earth, allowing very small features to be observed reliably on the first attempt. AEGIS consistently recognizes and selects the geological materials requested of it, parsing and interpreting geological scenes in tens to hundreds of seconds with very limited computing resources. Performance in autonomously selecting the most desired target material over the last 2.5 kilometers of driving into previously unexplored terrain exceeds 93 percent (where approximately 24 percent is expected without intelligent targeting), and all observations resulted in a successful geochemical observation. The system has substantially reduced lost time on the mission and markedly increased the pace of data collection with ChemCam. AEGIS autonomy has rapidly been adopted as an exploration tool by the mission scientists and has influenced their strategy for exploring the rover's environment.},
  clearance = {CL#17-2702},
  project = {rover},
  featured = 1,
}

Limitations on interplanetary communications create operations latencies and slow progress in planetary surface missions, with particular challenges to narrow-field-of-view science instruments requiring precise targeting. The AEGIS (Autonomous Exploration for Gathering Increased Science) autonomous targeting system has been in routine use on NASA's Curiosity Mars rover since May 2016, selecting targets for the ChemCam remote geochemical spectrometer instrument. AEGIS operates in two modes; in autonomous target selection, it identifies geological targets in images from the rover's navigation cameras, choosing for itself targets that match the parameters specified by mission scientists the most, and immediately measures them with ChemCam, without Earth in the loop. In autonomous pointing refinement, the system corrects small pointing errors on the order of a few milliradians in observations targeted by operators on Earth, allowing very small features to be observed reliably on the first attempt. AEGIS consistently recognizes and selects the geological materials requested of it, parsing and interpreting geological scenes in tens to hundreds of seconds with very limited computing resources. Performance in autonomously selecting the most desired target material over the last 2.5 kilometers of driving into previously unexplored terrain exceeds 93 percent (where approximately 24 percent is expected without intelligent targeting), and all observations resulted in a successful geochemical observation. The system has substantially reduced lost time on the mission and markedly increased the pace of data collection with ChemCam. AEGIS autonomy has rapidly been adopted as an exploration tool by the mission scientists and has influenced their strategy for exploring the rover's environment.

@article{chien-wagstaff-2017,
  author = {S. Chien and K. L. Wagstaff},
  title = {Robotic Space Exploration Agents},
  journal = {Science Robotics},
  year = {2017},
  month = {June},
  abstract = {By making their own exploration decisions, robotic spacecraft can conduct traditional science investigations more efficiently and even achieve otherwise impossible observations, such as responding to a short-lived plume at a comet millions of miles from Earth.},
  url = {http://robotics.sciencemag.org/cgi/content/full/2/7/eaan4831?ijkey=ygu9BARoFZfzo&keytype=ref&siteid=robotics},
  clearance = {CL#17-2089},
  featured = 1,
}

By making their own exploration decisions, robotic spacecraft can conduct traditional science investigations more efficiently and even achieve otherwise impossible observations, such as responding to a short-lived plume at a comet millions of miles from Earth.

@inproceedings{rabideau-benowitz-IWPSS-2017,
  author = {Gregg Rabideau and Ed Benowitz},
  title = {Prototyping an Onboard Scheduler for the Mars 2020 Rover},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/rabideau_iwpss2017_prototyping.pdf},
  clearance = {CL#17-2272},
  project = {rover, m2020},
}

@inproceedings{hernandez-garza-broschart-et-al-2017,
  author = {S. Hernandez and D. Garza and S. Broschart and S. Herzig and S. Chien},
  title = {Small Satellite Constellation to enable a lunar radio interferometer},
  booktitle = {Astrodynamics Specialist Conference, American Astronautical Society},
  year = {2017},
  month = {August},
  address = {Stevenson, WA},
  clearance = {CL#17-1731},
  project = {relic},
}

@inproceedings{castillo-rogez-fraeman-herzig-et-al-2017,
  author = {A. Fraeman and E. J. Wyatt and J. Lazio and J. Castillo-Rogez and S. Chien and S. Herzig and J. Gao and F. Alibay and K. Belov and D. Ellison and H. Kim and M. Troesch and W. Walsh},
  title = {Benefits Offered by a Network of CubeSat-Class Rovers for Planetary Cave Exploration},
  booktitle = {Low Cost Planetary Missions Workshop},
  year = {2017},
  month = {August},
  address = {Pasadena, CA},
  abstract = {The past decade has seen increasing interest in planetary cave exploration. Dozens of skylights have been found on Mars by the Mars Reconnaissance Orbiter and hundreds on the Moon from the Lunar Reconnaissance Orbiter. Pictures of lunar caves display stratification that provide an in-place record of the Moon's magmatic evolutionary history Martian caves may represent astrobiological sites that have offered shelters for past and possibly current life, and could serve as volatile traps that record Mars' climate evolution. Caves on both the Moon and Mars are exciting prospective habitats for future crewed missions because they likely offer radiation protection and a stable temperature environment Robotic planetary cave exploration would be challenging for a multitude of reasons.  Uncertainty in the target terrain requires robust mobility systems Communication between assets within a cave and to the surface would be difficult due to the chaotic signal propagation.  The absence of sunlight requires all power needed for instrument operations, data processing and communication to be brought into the cave We focus on utilizing a variety of assets to mitigate challenges related to communication and instrument operations while optimizing data acquisition and science data retrieval via an organized network We developed a set of science objectives and requirements for a reconnaissance mission concept to a Martian cave focused on mapping the cave geometry, composition, and measuring the temporal and spatial variability of cave environmental conditions (temperature, radiation and humidity). The proposed payload leverages recent or emerging miniaturized instruments developed for CubeSat-class deep space missions. The mild radiation and thermal environment expected in caves justifies the use of CubeSat-class instruments while the multiple assets provide redundancy We studied heterogeneous architectures where responsibilities (science telecom) are distributed among assets.  The conceptual DuAxel rover is assumed to be the carrier and telecom relay to the Martian orbiters and may also offer a computing node to support the smaller assets' semi-autonomous navigation inside the cave. Our study includes trade-offs between potential power sources, homogeneity and heterogeneity of the assets, as well as distribution of science instruments to optimize cost and achieved benefit.},
  project = {CaveRovers},
}

The past decade has seen increasing interest in planetary cave exploration. Dozens of skylights have been found on Mars by the Mars Reconnaissance Orbiter and hundreds on the Moon from the Lunar Reconnaissance Orbiter. Pictures of lunar caves display stratification that provide an in-place record of the Moon's magmatic evolutionary history Martian caves may represent astrobiological sites that have offered shelters for past and possibly current life, and could serve as volatile traps that record Mars' climate evolution. Caves on both the Moon and Mars are exciting prospective habitats for future crewed missions because they likely offer radiation protection and a stable temperature environment Robotic planetary cave exploration would be challenging for a multitude of reasons. Uncertainty in the target terrain requires robust mobility systems Communication between assets within a cave and to the surface would be difficult due to the chaotic signal propagation. The absence of sunlight requires all power needed for instrument operations, data processing and communication to be brought into the cave We focus on utilizing a variety of assets to mitigate challenges related to communication and instrument operations while optimizing data acquisition and science data retrieval via an organized network We developed a set of science objectives and requirements for a reconnaissance mission concept to a Martian cave focused on mapping the cave geometry, composition, and measuring the temporal and spatial variability of cave environmental conditions (temperature, radiation and humidity). The proposed payload leverages recent or emerging miniaturized instruments developed for CubeSat-class deep space missions. The mild radiation and thermal environment expected in caves justifies the use of CubeSat-class instruments while the multiple assets provide redundancy We studied heterogeneous architectures where responsibilities (science telecom) are distributed among assets. The conceptual DuAxel rover is assumed to be the carrier and telecom relay to the Martian orbiters and may also offer a computing node to support the smaller assets' semi-autonomous navigation inside the cave. Our study includes trade-offs between potential power sources, homogeneity and heterogeneity of the assets, as well as distribution of science instruments to optimize cost and achieved benefit.

@inproceedings{middleton-campbell-ong-et-al-IGARSS-2017,
  author = {E. Middleton and P. Campbell and L. Ong and D. Landis and Q. Zhang and C. Neigh and K. F. Huemmrich and S. Ungar and D. Mandl and S. Frye and V. Ly and P. Cappalaere and S. Chien and S. Franks and N. Pollack},
  title = {Hyperion: The first Global Orbital Spectrometer, Earth Observing One Satellite (2000-2017)},
  booktitle = {International Geoscience and Remote Sensing Symposium (IGARSS 2017)},
  year = {2017},
  month = {July},
  address = {Fort Worth, TX},
  project = {ase},
}

@inproceedings{wyatt-belov-burleigh-et-al-2017,
  author = {E. J. Wyatt and K. Belov and S. Burleigh and J. Castillo-Rogez and S. Chien and L. Clare and J. Lazio},
  title = {New Capabilities for Deep Space Robotic Exploration Enabled by Disruption Tolerant Networking},
  booktitle = {6th International Conference on Space Mission Challenges for Information Technology (SMC-IT 2017)},
  year = {2017},
  month = {September},
  address = {Alcala de Henares, Spain},
  pages = {1-6},
  abstract = {Disruption Tolerant Networking (DTN) is a term that is used both to describe network architectures in space as well as the protocol suite that implements key aspects of this functionality. Now that the core protocols have been defined and have been standardized, it is timely to pursue applying these protocols to enable new types of exploration where coordination among assets must occur without ground intervention. In order to do that, autonomy software applications must be developed to work in concert with the protocol layer to achieve the desired mission objectives. This paper describes key functionality of the protcol suite, autonomy software that is likely most useful in accomplishing mission objectives involving coordination and automated relay of information, mission concepts that could be enabled by space networking, and DTN development status for deep space applications.},
  doi = {10.1109/SMC-IT.2017.8},
  clearance = {CL#17-1063},
  project = {CaveRovers},
}

Disruption Tolerant Networking (DTN) is a term that is used both to describe network architectures in space as well as the protocol suite that implements key aspects of this functionality. Now that the core protocols have been defined and have been standardized, it is timely to pursue applying these protocols to enable new types of exploration where coordination among assets must occur without ground intervention. In order to do that, autonomy software applications must be developed to work in concert with the protocol layer to achieve the desired mission objectives. This paper describes key functionality of the protcol suite, autonomy software that is likely most useful in accomplishing mission objectives involving coordination and automated relay of information, mission concepts that could be enabled by space networking, and DTN development status for deep space applications.

@inproceedings{wyatt-castillo-rogez-chien-et-al-2017,
  author = {E. J. Wyatt and J. C. Castillo-Rogez and S. A. Chien and L. P. Clare and A. A. Fraeman and S. J. Herzig and I. A. Nesnas and J. Lazio},
  title = {Novel Planetary Science Enabled by Networked Constellations},
  booktitle = {Planetary Science Vision 2050 Workshop},
  year = {2017},
  month = {February},
  address = {NASA HQ, Washington, D. C.},
  clearance = {CL#16-6171},
  project = {relic CaveRovers},
}

@inproceedings{german-hand-mcdermott-et-al-2017,
  author = {C. R. German and K. P. Hand and J. M. McDermott and J. S. See-wald and J. C. Kinsey and A. D. Bowen and S. Chien and S. R. Schaffer and W. Bach and A. Boetius},
  title = {Oases for Life in Ice Covered Oceans},
  booktitle = {Astrobiology Science Conference},
  year = {2017},
  month = {April},
  address = {Mesa, AZ},
  project = {ice_covered_oceans},
}

@article{gao-chien-2017,
  author = {Y. Gao and S. Chien},
  title = {Review on space robotics: Toward top-level science through space exploration},
  journal = {Science Robotics},
  year = {2017},
  month = {June},
  abstract = {Robotics and autonomous systems have been instrumental to space exploration by enabling scientific breakthroughs and by fulfilling human curiosity and ambition to conquer new worlds. We provide an overview of space robotics as a rapidly emerging field, covering basic concepts, definitions, historical context, and evolution. We further present a technical road map of the field for the coming decades, taking into account major challenges and priorities recognized by the international space community. Space robotics represents several key enablers to a wide range of future robotic and crewed space missions as well as opportunities for knowledge and technology transfer to many terrestrial sectors. In the greater humanitarian context, space robotics inspires both current and future generations to exploration and critical study of science, technology, engineering, and mathematics.},
  clearance = {CL#17-2439},
  featured = 1,
}

Robotics and autonomous systems have been instrumental to space exploration by enabling scientific breakthroughs and by fulfilling human curiosity and ambition to conquer new worlds. We provide an overview of space robotics as a rapidly emerging field, covering basic concepts, definitions, historical context, and evolution. We further present a technical road map of the field for the coming decades, taking into account major challenges and priorities recognized by the international space community. Space robotics represents several key enablers to a wide range of future robotic and crewed space missions as well as opportunities for knowledge and technology transfer to many terrestrial sectors. In the greater humanitarian context, space robotics inspires both current and future generations to exploration and critical study of science, technology, engineering, and mathematics.

@article{thompson-chao-chien-et-al-2017,
  author = {Andrew F. Thompson and Yi Chao and Steve Chien and James Kinsey and Mar M. Flexas and Andrew Branch and Selina Chu and Martina Troesch and Brian Claus and James Kepper and John Farrara and David Fratantoni},
  title = {Satellites to Seafloor: Towards Fully Autonomous Ocean Sampling},
  journal = {Oceanography},
  year = {2017},
  month = {June},
  volume = {30 (2)},
  abstract = { Future ocean observing systems will rely heavily on autonomous vehicles to achieve the persistent and heterogeneous measurements needed to understand the ocean's impact on the climate system. The day-to-day maintenance of these arrays will become increasingly challenging if significant human resources, such as manual piloting, are required. For this reason techniques need to be developed that permit autonomous determination of sampling directives based on science goals and responses to in situ remote-sensing, and model-derived information. Techniques that can accommodate large arrays of assets and permit sustained observations of rapidly evolving ocean properties are especially needed for capturing interactions between physical circulation and biogeochemical cycling Here we document the first field program of the Satellites to Seafloor project, designed to enable a closed loop of numerical model prediction vehicle path-planning, in situ path implementation, data collection, and data assimilation for future model predictions. We present results from the first of two field programs carried out in Monterey Bay, California over a period of three months in 2016. While relatively modest in scope this approach provides a step toward an observing array that makes use of multiple information streams to update and improve sampling strategies without human intervention. },
  url = {http://tos.org/oceanography/article/satellites-to-seafloor-toward-fully-autonomous-ocean-sampling},
  clearance = {CL#17-2890},
  project = {keck_marine},
}

Future ocean observing systems will rely heavily on autonomous vehicles to achieve the persistent and heterogeneous measurements needed to understand the ocean's impact on the climate system. The day-to-day maintenance of these arrays will become increasingly challenging if significant human resources, such as manual piloting, are required. For this reason techniques need to be developed that permit autonomous determination of sampling directives based on science goals and responses to in situ remote-sensing, and model-derived information. Techniques that can accommodate large arrays of assets and permit sustained observations of rapidly evolving ocean properties are especially needed for capturing interactions between physical circulation and biogeochemical cycling Here we document the first field program of the Satellites to Seafloor project, designed to enable a closed loop of numerical model prediction vehicle path-planning, in situ path implementation, data collection, and data assimilation for future model predictions. We present results from the first of two field programs carried out in Monterey Bay, California over a period of three months in 2016. While relatively modest in scope this approach provides a step toward an observing array that makes use of multiple information streams to update and improve sampling strategies without human intervention.

@inproceedings{gaines-doran-justice-et-al-IWPSS-2017,
  author = {Daniel Gaines and Gary Doran and Heather Justice and Gregg Rabideau and Steve Schaffer and Vandana Verma and Kiri Wagstaff and Ashwin Vasavada and William Huffman and Robert Anderson and Ryan Mackey and Tara Estlin},
  title = {A Case Study of Productivity Challenges in Mars Science Laboratory Operations},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/gaines_iwpss2017_case.pdf},
  clearance = {CL#17-2203},
  project = {srr},
}

@inproceedings{pinover-johnston-lee-IWPSS-2017,
  author = {Kaley Pinover and Mark D. Johnston and Carlyn Lee},
  title = {Optimizing SmallSat Scheduling for NASA's Deep Space Network},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/pinover_iwpss2017_optimizing.pdf},
  clearance = {CL#17-2524},
  project = {SSS},
}

@inproceedings{gaines-rabideau-doran-et-al-IWPSS-2017,
  author = {Daniel Gaines and Gregg Rabideau and Gary Doran and Steve Schaffer and Vincent Wong and Ashwin Vasavada and Robert Anderson},
  title = {Expressing Campaign Intent to Increase Productivity of Planetary Exploration Rovers},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/gaines_iwpss2017_expressing.pdf},
  clearance = {CL#17-2487},
  project = {srr},
}

@inproceedings{lewellen-trowbridge-shao-et-al-IWPSS-2017,
  author = {Garrett Lewellen and Michael Trowbridge and Elly Shao and Christopher Davies and Russell Knight},
  title = {Estimating Time to Image Areas with Steerable 2D Framing Sensors},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/lewellen_iwpss2017_estimating.pdf},
  clearance = {CL#17-2530},
  project = {EagleEye},
}

@inproceedings{verma-gaines-rabideau-et-al-IWPSS-2017,
  author = {Vandi Verma and Dan Gaines and Gregg Rabideau and Steve Schaffer and Rajeev Joshi},
  title = {Autonomous Science Restart for the Planned Europa Mission with Lightweight Planning and Execution},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/verma_iwpss2017_autonomous.pdf},
  clearance = {CL#17-2299},
  project = {mexec},
}

@inproceedings{trowbridge-doubleday-IWPSS-2017,
  author = {Michael Trowbridge and Joshua R. Doubleday},
  title = {Intermediate Fidelity Solid State Recorder Modeling for NISAR},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/trowbridge_iwpss2017_intermediate.pdf},
  clearance = {CL#17-2537},
  project = {clasp},
}

@inproceedings{troesch-chien-ferguson-IWPSS-2017,
  author = {Martina Troesch and Steve Chien and Eric Ferguson},
  title = {Using Automated Scheduling to Assess Coverage for Europa Clipper and JUpiter ICy moons Explorer},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  abstract = { We describe the use of an automated scheduling system to assess mapping coverage for space missions. This tool uses a gridded representation of target body surface regions of interest to calculate surface coverage based on science objectives, such as distance to target and lighting conditions, and spacecraft constraints, such as data volume The science objectives and constraints are modelled in a greedy optimization, scheduling algorithm that generates observation schedules. We demon- strate the application of this tool to evaluating achievement of mission science criteria for the planned Europa Clipper mission and the JUpiter ICy moons Explorer (JUICE). },
  url = {https://ai.jpl.nasa.gov/public/papers/troesch_iwpss2017_juice.pdf},
  clearance = {CL#17-2618},
  project = {clasp},
}

We describe the use of an automated scheduling system to assess mapping coverage for space missions. This tool uses a gridded representation of target body surface regions of interest to calculate surface coverage based on science objectives, such as distance to target and lighting conditions, and spacecraft constraints, such as data volume The science objectives and constraints are modelled in a greedy optimization, scheduling algorithm that generates observation schedules. We demon- strate the application of this tool to evaluating achievement of mission science criteria for the planned Europa Clipper mission and the JUpiter ICy moons Explorer (JUICE).

@inproceedings{lewellen-davies-byon-et-al-IWPSS-2017,
  author = {Garrett Lewellen and Christopher Davies and Amos Byon and Russell Knight and Elly Shao and Daniel Tran and Michael Trowbridge},
  title = {A Hybrid Traveling Salesman Problem - Squeaky Wheel Optimization Planner for Earth Observational Scheduling},
  booktitle = {International Workshop on Planning and Scheduling for Space (IWPSS 2017)},
  year = {2017},
  month = {June},
  address = {Pittsburgh, PA},
  url = {https://ai.jpl.nasa.gov/public/papers/lewellen_iwpss2017_hybrid.pdf},
  clearance = {CL#17-2697},
  project = {EagleEye},
}

@inproceedings{branch-troesch-flexas-et-al-2017,
  author = {A. Branch and M. Troesch and M. Flexas and A. Thompson and J. Ferrara and Y. Chao and S. Chien},
  title = {Station Keeping with an Autonomous Underwater Glider Using a Predictive Model of Ocean Currents},
  booktitle = {AI in the Oceans and Space Workshop, International Joint Conference on Artificial Intelligence (IJCAI 2017)},
  year = {2017},
  month = {August},
  address = {Melbourne, Australia},
  abstract = { We investigate the use of an autonomous underwater glider as a platform for a virtual mooring. Our approach uses a simple vehicle motion model, a predictive model of ocean currents and a greedy search algorithm in order to simulate possible actions available to the vehicle and select an action to minimize the distance from the target point. Results from a 19 day experiment in October 2016 near Monterey Bay are presented where we test our control algorithm as well as investigate the effect of a glider's dive profile on its ability to act as a virtual mooring. },
  url = {https://ai.jpl.nasa.gov/public/papers/branch_ijcai2017_station.pdf},
  clearance = {CL#17-4088},
  project = {SWOT_station},
}

We investigate the use of an autonomous underwater glider as a platform for a virtual mooring. Our approach uses a simple vehicle motion model, a predictive model of ocean currents and a greedy search algorithm in order to simulate possible actions available to the vehicle and select an action to minimize the distance from the target point. Results from a 19 day experiment in October 2016 near Monterey Bay are presented where we test our control algorithm as well as investigate the effect of a glider's dive profile on its ability to act as a virtual mooring.

@inproceedings{johnston-wyatt-2017,
  author = {M. Johnston and E. J. Wyatt},
  title = {AI and Autonomy Initiatives for NASA's Deep Space Network (DSN)},
  booktitle = {AI in the Oceans and Space Workshop, International Joint Conference on Artificial Intelligence (IJCAI 2017)},
  year = {2017},
  month = {August},
  address = {Melbourne, Australia},
  url = {https://ai.jpl.nasa.gov/public/papers/johnston_ijcai2017_network.pdf},
  clearance = {CL#17-4024},
  project = {SSS},
}

@article{rabideau-chien-galer-et-al-2017,
  author = {G. Rabideau and S. Chien and M. Galer and F. Nespoli and M. Costa},
  title = {Managing Spacecraft Memory Buffers with Concurrent Data Collection and Downlink},
  journal = {Journal of Aerospace Information Systems (JAIS)},
  year = {2017},
  month = {December},
  doi = {http://arc.aiaa.org/doi/abs/10.2514/1.I010544},
  organization = {AIAA},
  abstract = {Space mission planning/scheduling is determining the set of spacecraft activities to meet mission objectives while respecting mission constraints. One important category of mission constraints is data management. As the spacecraft acquires data via science instruments and engineering telemetry, it must store the data on board until it is able to downlink the data to ground communications stations. Because onboard storage and communication opportunities are often limited, this can be a challenging task. This paper first describes the general problem of onboard memory management for spacecraft that allow concurrent data collection and downlink activities. Then, a fast, intuitive heuristic is presented for solving this problem, and its use on the Rosetta comet rendezvous mission is evaluated. Finally, different local heuristics are compared for a greedy search to a global graph-based solution, measuring performance in terms of runtime and robustness to downlink buffer overflow. The results show that local heuristics can produce solutions that are comparable, and often better than, solutions from a global formulation.},
  url = {http://arc.aiaa.org/doi/abs/10.2514/1.I010544},
  clearance = {CL#17-4479},
  project = {rosetta},
  featured = 1,
}

Space mission planning/scheduling is determining the set of spacecraft activities to meet mission objectives while respecting mission constraints. One important category of mission constraints is data management. As the spacecraft acquires data via science instruments and engineering telemetry, it must store the data on board until it is able to downlink the data to ground communications stations. Because onboard storage and communication opportunities are often limited, this can be a challenging task. This paper first describes the general problem of onboard memory management for spacecraft that allow concurrent data collection and downlink activities. Then, a fast, intuitive heuristic is presented for solving this problem, and its use on the Rosetta comet rendezvous mission is evaluated. Finally, different local heuristics are compared for a greedy search to a global graph-based solution, measuring performance in terms of runtime and robustness to downlink buffer overflow. The results show that local heuristics can produce solutions that are comparable, and often better than, solutions from a global formulation.

@inproceedings{chien-hyspiri-symp-2017,
  author = {S. Chien and M. Troesch and D. Tran and S. Schaffer and D. R. Thompson and R. Green and K. Wagstaff and A. Altinok and U. Rebbapragada and D. Mandl and E. Middleton and S. Ungar and L. Ong and P. Campbell and B. Trout and J. Hengemihle},
  title = {Results from ALI and OLI Multispectral Band Synthesis, Machine Learning Classificaion, and Salience onboard the Earth Observing One Mission},
  booktitle = {Workshop on: Global Earth Imaging Spectroscopy and Thermal Infrared Measurements (HyspIRI) NASA Decadal Survey Mission Concept},
  year = {2017},
  month = {October},
  address = {Pasadena, CA},
  clearance = {CL#17-5314},
  project = {HyspIRI},
}