Doyle, Richard
Advancing the Scientific Frontier with Increasingly Autonomous Systems
Amini, Rashied, Azari, Abigail, Bhaskaran, Shyam, Beauchamp, Patricia, Castillo-Rogez, Julie, Castano, Rebecca, Chung, Seung, Day, John, Doyle, Richard, Feather, Martin, Fesq, Lorraine, Frank, Jeremy, Furlong, P. Michael, Ingham, Michel, Kennedy, Brian, Kolcio, Ksenia, Nesnas, Issa, Rasmussen, Robert, Reeves, Glenn, Sorice, Cristina, Theiling, Bethany, Wyatt, Jay
A close partnership between people and partially autonomous machines has enabled decades of space exploration. But to further expand our horizons, our systems must become more capable. Increasing the nature and degree of autonomy - allowing our systems to make and act on their own decisions as directed by mission teams - enables new science capabilities and enhances science return. The 2011 Planetary Science Decadal Survey (PSDS) and on-going pre-Decadal mission studies have identified increased autonomy as a core technology required for future missions. However, even as scientific discovery has necessitated the development of autonomous systems and past flight demonstrations have been successful, institutional barriers have limited its maturation and infusion on existing planetary missions. Consequently, the authors and endorsers of this paper recommend that new programmatic pathways be developed to infuse autonomy, infrastructure for support autonomous systems be invested in, new practices be adopted, and the cost-saving value of autonomy for operations be studied.
Highly Autonomous Systems Workshop
Doyle, Richard, Rasmussen, Robert, Man, Guy, Patel, Keyur
Researchers and technology developers from the National Aeronautics and Space Administration (NASA), other government agencies, academia, and industry recently met in Pasadena, California, to take stock of past and current work and future challenges in the application of AI to highly autonomous systems. The meeting was catalyzed by new opportunities in developing autonomous spacecraft for NASA and was in part a celebration of the fictional birth year of the HAL-9000 computer.
Highly Autonomous Systems Workshop
Doyle, Richard, Rasmussen, Robert, Man, Guy, Patel, Keyur
Researchers and technology developers from the National Aeronautics and Space Administration (NASA), other government agencies, academia, and industry recently met in Pasadena, California, to take stock of past and current work and future challenges in the application of AI to highly autonomous systems. The meeting was catalyzed by new opportunities in developing autonomous spacecraft for NASA and was in part a celebration of the fictional birth year of the HAL-9000 computer.
Making an Impact: Artificial Intelligence at the Jet Propulsion Laboratory
Chien, Steve, DeCoste, Dennis, Doyle, Richard, Stolorz, Paul
The National Aeronautics and Space Administration (NASA) is being challenged to perform more frequent and intensive space-exploration missions at greatly reduced cost. Nowhere is this challenge more acute than among robotic planetary exploration missions that the Jet Propulsion Laboratory (JPL) conducts for NASA. This article describes recent and ongoing work on spacecraft autonomy and ground systems that builds on a legacy of existing success at JPL applying AI techniques to challenging computational problems in planning and scheduling, real-time monitoring and control, scientific data analysis, and design automation.
Making an Impact: Artificial Intelligence at the Jet Propulsion Laboratory
Chien, Steve, DeCoste, Dennis, Doyle, Richard, Stolorz, Paul
The National Aeronautics and Space Administration (NASA) is being challenged to perform more frequent and intensive space-exploration missions at greatly reduced cost. Nowhere is this challenge more acute than among robotic planetary exploration missions that the Jet Propulsion Laboratory (JPL) conducts for NASA. This article describes recent and ongoing work on spacecraft autonomy and ground systems that builds on a legacy of existing success at JPL applying AI techniques to challenging computational problems in planning and scheduling, real-time monitoring and control, scientific data analysis, and design automation.