Benjamin Cichy

Using Autonomy Flight Software to Improve Science Return on Earth Observing One

NASA’s Earth Observing One Spacecraft (EO-1) has been adapted to host an advanced suite of onboard autonomy software designed to dramatically improve the quality and timeliness of science-data returned from remote-sensing missions. The Autonomous Sciencecraft Experiment (ASE) enables the spacecraft to autonomously detect and respond to dynamic scientifically interesting events observed from EO-1’s low earth orbit. ASE includes software systems that perform science data analysis, mission planning, and runtime robust execution. In this article we describe the autonomy flight software, as well as innovative solutions to the challenges presented by autonomy, reliability, and limited computing resources.

An autonomous earth-observing sensorWeb

We describe a network of sensors linked by software and the Internet to an autonomous satellite observation response capability. This system of systems is designed with a flexible, modular, architecture to facilitate expansion in sensors, customization of trigger conditions, and customization of responses. This system has been used to implement a global surveillance program of science phenomena including: volcanoes, flooding, cryosphere events, and atmospheric phenomena. In this paper we describe the importance of the earth observing sensorweb application as well as overall architecture for the system of systems.

The EO-1 Autonomous Science Agent

An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe the constraints and how they were addressed in our agent design, validation, and deployment.

Lessons learned from autonomous sciencecraft experiment

An Autonomous Science Agent has been flying onboard the Earth Observing One Spacecraft since 2003. This software enables the spacecraft to autonomously detect and responds to science events occurring on the Earth such as volcanoes, flooding, and snow melt. The package includes AI-based software systems that perform science data analysis, deliberative planning, and run-time robust execution. This software is in routine use to fly the EO-1 mission. In this paper we briefly review the agent architecture and discuss lessons learned from this multi-year flight effort pertinent to deployment of software agents to critical applications.

Autonomous science agents and sensor Webs: EO-1 and beyond

An autonomous science agent, part of the New Millennium Space Technology 6 Project is currently flying onboard the Earth Observing One (EO-1) spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. This software has demonstrated the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data. As a result, ground-based mission planning and analysis functions have been greatly simplified, thus reducing operations cost. We describe several technology infusions applications being developed. We also describe how the software has been used in conjunction with other satellites and ground sensors to form an autonomous sensor-Web

Mission operations of Earth Observing-1 with onboard autonomy

Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the prior, labor and knowledge intensive mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the new autonomous operations as part of the Autonomous Sciencecraft Experiment (ASE)

An autonomous Earth observing sensorweb

We describe a network of sensors linked by software and the Internet to an autonomous satellite observation response capability. This sensor network is designed with a flexible, modular, architecture to facilitate expansion in sensors, customization of trigger conditions, and customization of responses. This system has been used to implement a global surveillance program of multiple science phenomena including: volcanoes, flooding, cryosphere events, and atmospheric phenomena. In this paper we describe the importance of the Earth observing sensorWeb application as well as overall architecture for the network

Intelligent systems in space : the EO-1 Autonomous Sciencecraft

The Autonomous Sciencecraft Software (ASE) is currently flying onboard the Earth Observing One (EO-1) Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and runtime robust execution. Because of the deployment to the EO-1 spacecraft, the ASE software has stringent constraints of autonomy and limited computing resources. We describe these constraints and how they are reflected in our operations approach. A summary of the final results of the experiment is also included. This software has demonstrated the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data. As a result, ground-based mission planning and analysis functions have been greatly simplified, thus reducing operations cost.

The autonomous sciencecraft embedded systems architecture

An Autonomous Science Agent has been flying onboard the Earth Observing One spacecraft since 2003. This software enables the spacecraft to autonomously detect and responds to science events occurring on the Earth such as volcanoes, flooding, and snow melt. This agent includes artificial intelligence software systems that perform science data analysis, deliberative planning, and run-time robust execution. This software is in routine use to fly the EO-1 mission. In this paper we discuss the architecture used to integrate these systems and lessons learned from its multi-year flight on EO-1.

Preliminary results of the Autonomous Sciencecraft Experiment

The Autonomous Sciencecraft Experiment (ASE) operates onboard the Earth Orbiter 1 mission in 2004. The ASE software uses onboard continuous planning, robust task and goal-based execution, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In This work we discuss how these AI technologies are synergistically integrated in multi-layer control architecture to enable a virtual spacecraft science agent. We also present the preliminary results from flight validation of this experiment. This software demonstrates the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data. As a result, ground-based mission planning and analysis functions were simplified, thus reducing operations cost.