Engineering topics

Sherwood, Robert L.

Publications and source records attributed to Sherwood, Robert L..

5 records

NASA NTRS2005

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.

Earth Observing One (EO-1) Spacecraft↗

NASA NTRS2005

Mars Aeronomy Explorer (MAX): Study Employing Distributed Micro-Spacecraft

An overview of a Mars Aeronomy Explorer (MAX) mission design study performed at NASA's Jet Propulsion Laboratory is presented herein. The mission design consists of ten micro-spacecraft orbiters launched on a Delta IV to Mars polar orbit to determine the spatial, diurnal and seasonal variation of the constituents of the Martian upper atmosphere and ionosphere over the course of one Martian year. The spacecraft are designed to allow penetration of the upper atmosphere to at least 90 km. This property coupled with orbit precession will yield knowledge of the nature of the solar wind interaction with Mars, the influence of the Mars crustal magnetic field on ionospheric processes, and the measurement of present thermal and nonthermal escape rates of atmospheric constituents. The mission design incorporates alternative design paradigms that are more appropriate for-and in some cases motivate-distributed micro-spacecraft. These design paradigms are not defined by a simple set of rules, but rather a way of thinking about the function of instruments, mission reliability/risk, and cost in a systemic framework.

Mars↗

NASA NTRS2004

Onboard Autonomy on the Earth Observing One Mission

The Earth Observing One Spacecraft is currently flying The Autonomous Sciencecraft Experiment (ASE) - onboard autonomy software to improve science return. The ASE software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. ASE includes software systems that perform science data analysis, mission planning, and run-time robust execution. In this article we describe the autonomy flight software and how it enables a new paradigm of autonomous science and mission operations.

autonomy↗

NASA NTRS2004

Preliminary results of the autonomous sciencecraft experiment

The Autonomous Sciencecraft Experiment (ASE) will operate onboard the Earth Orbiter 1 mission in 2003. The ASE software uses onboard continuous planning, robust task and goal-based execution, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in multilayer control architecture to enable a virtual spacecraft science agent.

Rabideau, Gregg↗

NASA NTRS1997

Automating the Process of Optimization in Spacecraft Design

Spacecraft design optimization is a difficult problem, due to the complexity of optimization cost surfaces, and human expertise in optimization that is necessary in order to achieve good results. In this paper, we propose the use of a set of generic, metaheuristic optimization algorithms (e.g., generic algorithms, simulated annealing), which is configured for a particular optimization problem by an adaptive problem solver based on artificial intelligence and machine learning techniques. We describe work in progress on OASIS, a system for adaptive problem solving based on these principles.

optimization↗