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Chien, Steve

Publications and source records attributed to Chien, Steve.

At least 181 records · Page 10

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↗

Software for Automation of Real-Time Agents, Version 2

Version 2 of Closed Loop Execution and Recovery (CLEaR) has been developed. CLEaR is an artificial intelligence computer program for use in planning and execution of actions of autonomous agents, including, for example, Deep Space Network (DSN) antenna ground stations, robotic exploratory ground vehicles (rovers), robotic aircraft (UAVs), and robotic spacecraft. CLEaR automates the generation and execution of command sequences, monitoring the sequence execution, and modifying the command sequence in response to execution deviations and failures as well as new goals for the agent to achieve. The development of CLEaR has focused on the unification of planning and execution to increase the ability of the autonomous agent to perform under tight resource and time constraints coupled with uncertainty in how much of resources and time will be required to perform a task. This unification is realized by extending the traditional three-tier robotic control architecture by increasing the interaction between the software components that perform deliberation and reactive functions. The increase in interaction reduces the need to replan, enables earlier detection of the need to replan, and enables replanning to occur before an agent enters a state of failure.

Fisher, Forest↗

An Expert System for Autonomous Spacecraft Control

The Autonomous Sciencecraft Experiment (ASE), part of the New Millennium Space Technology 6 Project, is flying onboard the Earth Orbiter 1 (EO-1) mission. The ASE software enables EO-1 to autonomously detect and respond to science events such as: volcanic activity, flooding, and water freeze/thaw. ASE uses classification algorithms to analyze imagery onboard to detect chang-e and science events. Detection of these events is then used to trigger follow-up imagery. Onboard mission planning software then develops a response plan that accounts for target visibility and operations constraints. This plan is then executed using a task execution system that can deal with run-time anomalies. In this paper we describe the autonomy flight software and how it enables a new paradigm of autonomous science and mission operations. We will also describe the current experiment status and future plans.

utonomy flight software↗

Safe Agents in Space: Preventing and Responding to Anomalies in the Autonomous Sciencecraft Experiment

This paper describes the design of the Autonomous Sciencecraft Experiment, a software agent that has been running on-board the EO-I spacecraft since 2003. The agent recognizes science events, retargets the spacecraft to respond to the science events, and reduces data downlink to only the highest value science data. The autonomous science agent was designed using a layered architectural approach with specific redundant safeguards to reduce the risk of an agent malfUnction to the EO-I spacecraft. The agent was designed to be "safe" by first preventing anomalies, then by automatically detecting and responding to them when possible. This paper describes elements of the design that increase the safety of the agent, the anomalies that occurred during the experiment, and how the agent responded to these anomalies.

autonomous science agent↗

Centralized Planning for Multiple Exploratory Robots

A computer program automatically generates plans for a group of robotic vehicles (rovers) engaged in geological exploration of terrain. The program rapidly generates multiple command sequences that can be executed simultaneously by the rovers. Starting from a set of high-level goals, the program creates a sequence of commands for each rover while respecting hardware constraints and limitations on resources of each rover and of hardware (e.g., a radio communication terminal) shared by all the rovers. First, a separate model of each rover is loaded into a centralized planning subprogram. The centralized planning software uses the models of the rovers plus an iterative repair algorithm to resolve conflicts posed by demands for resources and by constraints associated with the all the rovers and the shared hardware. During repair, heuristics are used to make planning decisions that will result in solutions that will be better and will be found faster than would otherwise be possible. In particular, techniques from prior solutions of the multiple-traveling- salesmen problem are used as heuristics to generate plans in which the paths taken by the rovers to assigned scientific targets are shorter than they would otherwise be.

Estlin, Tara↗

New millennium program ST6: autonomous technologies for future NASA spacecraft

The purpose of NASA's New Millennium Program (NMP) is to validate advanced technologies in space and thus lower the risk for the first mission user. The focus of NMP is only on those technologies which need space environment for proper validation. The ST6 project has developed two advanced, experimental technologies for use on spacecraft of the future. These technologies are the Autonomous Sciencecraft Experiment and the Inertial Stellar Compass. These technologies will improve spacecraft's ability to: make decisions on what information to gather and send back to the ground, determine its own attitude and adjust its pointing.

ST6↗

Automated Planning and Scheduling for Space Mission Operations

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

scheduling↗

Sensor Webs: Autonomous Rapid Response to Monitor Transient Science Events

To better understand how physical phenomena, such as volcanic eruptions, evolve over time, multiple sensor observations over the duration of the event are required. Using sensor web approaches that integrate original detections by in-situ sensors and global-coverage, lower-resolution, on-orbit assets with automated rapid response observations from high resolution sensors, more observations of significant events can be made with increased temporal, spatial, and spectral resolution. This paper describes experiments using Earth Observing 1 (EO-1) along with other space and ground assets to implement progressive mission autonomy to identify, locate and image with high resolution instruments phenomena such as wildfires, volcanoes, floods and ice breakup. The software that plans, schedules and controls the various satellite assets are used to form ad hoc constellations which enable collaborative autonomous image collections triggered by transient phenomena. This software is both flight and ground based and works in concert to run all of the required assets cohesively and includes software that is model-based, artificial intelligence software.

Mandl, Dan↗

Towards Onboard Orbital Tracking of Seasonal Polar Volatiles on Mars

Current conditions on Mars support both a residual polar cap, composed mainly of water ice, and a seasonal cap, composed of CO2, which appears and disappears each winter. Kieffer and Titus characterized the recession of the seasonal south polar cap using an arctangent curve fit based on data from the Thermal Emission Spectrometer on Mars Global Surveyor [1]. They also found significant interannual deviations, at the regional scale, in the recession rate [2]. Further observations will enable the refinement of our models of polar cap evolution in both hemispheres. We have developed the Bimodal Image Temperature (BIT) Histogram Analysis method for the automated detection and tracking of the seasonal polar ice caps on Mars. It is specifically tailored for possible use onboard a spacecraft. We have evaluated BIT on uncalibrated data collected by the Thermal Emission Imaging System (THEMIS) instrument [3] on the Mars Odyssey spacecraft. In this paper, we focus on the northern seasonal cap, but our approach is directly applicable to the future analysis of the southern seasonal ice cap as well.

Wagstaff, Kiri L.↗

Safe Agents in Space: Lessons from the Autonomous Sciencecraft Experiment

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 these constraints and how they are reflected in our agent architecture.

Eatth Observing One Spacecraft↗

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↗

The autonomous sciencecraft experiment onboard the EO-1 spacecraft

The Autonomous Sciencecraft Experiment (ASE), currently flying onboard the Earth Observing-1 (EO-I) spacecraft, integrates several autonomy software technologies enabling autonomous science analysis and mission planning. The experiment demonstrates the potential for future space missions to use onboard decision-making to respond autonomously to capture short-lived science phenomena. The AAAI software demonstration will consist of two sections: a real-time display of an ASE-commanded ground contact from the EO-1 spacecraft, and a simulation of the full ASE autonomous science-response scenario.

Earth Observatory (EO)↗

DEMO: the Autonomous Sciencecraft Experiment onboard the EO-1 spacecraft

The Autonomous Sciencececraft Experiment (ASE), currently flying onboard the Earth Observing-1 (EO-1) spacecraft, integrates several autnomoy software technologies enabling autnomous science analysis and mission planning. The experiment demonstrates the potential for future space missions to use onboard decision-making to respond autonomously to capture short-lived science phenomena. The AAAI software demonstration will consist of two sections: a real-time display of an ASE-commanded ground contact from the EO-1 spacecraft, and a simulation of the full ASE autonomous science-response scenario.

EO-1 spacecraft↗