The Techsat-21 autonomous space science agent

Chien, Steve; Sherwood, Rob; Rabideau, Gregg; Castaño, Rebecca; Davies, A. G.; Burl, Michael C.; Knight, Russell; Stough, T.; Roden, J.; Zetocha, Paul; Wainwright, Ross; Klupar, Pete; Gaasbeck, Jim Van; Cappelaere, Pat; Oswald, Dean

doi:10.1145/544862.544880

Cited by 31 publications

(25 citation statements)

References 5 publications

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“…Both are multispacecraft experiments that feature onboard decision-making capabilities. 10 The onboard Continuous Activity Scheduling Planning Execution and Replanning software interacts with the Spacecraft Command Language to control the spacecraft. The Casper planner plans continuously to enable the spacecraft to respond to mission anomalies and opportunities.…”

Section: Uncrewed Spacecraft and Roversmentioning

confidence: 99%

A day in an astronaut's life: reflections on advanced planning and scheduling technology

Kortenkamp

2003

IEEE Intell. Syst.

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This installment of the AI in Space department looks at the process NASA uses to plan and execute an astronaut's "day in the life." As I do so, I will examine new planning and scheduling technologies recently presented at the Third International NASA Workshop on Planning and Scheduling for Space, held in Houston last October, and show how they might affect future Space Station astronauts. Pre-increment planning phaseStarting a year before the Space Station crew arrives, the pre-increment mission-planning phase involves accepting input from a variety of sources, including the international partners, public affairs department, and scientists with experimental payloads, among others. A detailed schedule of the crew's activities results. At the heart of all plan development is a single relational database at NASA Johnson Space Center (see Figure 1). A planning and scheduling software application called the consolidated planning system provides resource and constraint checking of the database's data. The CPS tracks such resources as crew, power, communications bandwidth, and consumables. The construction of a pre-increment plan is still largely a manual process, consuming huge numbers of work hours.Changing this process from a mostly manual to a more automated one will require significant advances in planning and scheduling software. Because humans will always be part of the planning process, especially to resolve political issues, any deployed system must exhibit mixedinitiative interaction, whereby automated software and human experts collaborate to create a plan. 1 During the recent NASA Workshop on Planning and Scheduling for Space, James Allen of the University of Rochester presented a paper on "Human-Machine Collaborative Planning" that discussed an explicit problem-solving level to mediate between the human-computer interaction and the underlying automated plan reasoners, bridging the gap between human and automated planning. 2 In his approach, mission planners would use natural language and graphical interfaces to input objectives they wish to achieve and constraints on possible solutions. Mission planners could build a plan incrementally, adding or subtracting constraints as necessary or suggesting potential solutions. The underlying plan reasoners would then decompose objectives into tasks, check constraints, and optimize resources, returning the incremental plan to the mission planners.In "Passat: A User-Centric Planning Framework," Karen Myers from SRI International discussed a framework that provides a set of plan editing and manipulation capabilities to support novice users in creating and modifying plans. 3 The Passat system builds upon a library of predefined templates that encode task networks describing standard operating procedures and previous cases. Users can select from these templates during plan development, with the system providing various forms of automated Previously in these pages I've made the observation that planning and scheduling technology often provides the core capability of a spa...

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Section: Uncrewed Spacecraft and Roversmentioning

confidence: 99%

A day in an astronaut's life: reflections on advanced planning and scheduling technology

Kortenkamp

2003

IEEE Intell. Syst.

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“…Invariably, those activities are subject to a variety of temporal constraints, such as release times, deadlines and precedence constraints. In addition, in some domains, the agent may control the starting times for actions, but not their durations (Chien et al, 2002;Hunsberger et al, 2012). For a simple example, I may control the starting time for my taxi ride to the airport, but not its duration.…”

Section: Introductionmentioning

confidence: 99%

A Faster Algorithm for Checking the Dynamic Controllability of Simple Temporal Networks with Uncertainty

Hunsberger

2014

Proceedings of the 6th International Conference on Agents and Artificial Intelligence

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Abstract:A Simple Temporal Network (STN) is a structure containing time-points and temporal constraints that an agent can use to manage its activities. A Simple Temporal Network with Uncertainty (STNU) augments an STN to include contingent links that can be used to represent actions with uncertain durations. The most important property of an STNU is whether it is dynamically controllable (DC)-that is, whether there exists a strategy for executing its time-points such that all constraints will necessarily be satisfied no matter how the contingent durations happen to turn out (within their known bounds). The fastest algorithm for checking the dynamic controllability of STNUs reported in the literature so far is the O(N 4 )-time algorithm due to Morris. This paper presents a new DC-checking algorithm that empirical results confirm is faster than Morris' algorithm, in many cases showing an order of magnitude speed-up. The algorithm employs two novel techniques. First, new constraints generated by propagation are immediately incorporated into the network using a technique called rotating Dijkstra. Second, a heuristic that exploits the nesting structure of certain paths in the STNU graph is used to determine a good order in which to process the contingent links during constraint propagation.

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“…7) This cycle is then repeated on subsequent observations. The basic software architecture used by ASE on EO-1 has been previously described, 3,18 thus here we concentrate on the overall system -how the components work together to achieve the closed loop science response as well as how the software was modified to deal with the unique challenges of flight on EO-1 (most of which apply to other space missions).…”

Section: Introductionmentioning

confidence: 99%

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

Chien¹,

Sherwood²,

Tran³

et al. 2005

Journal of Aerospace Computing, Information, and Communication

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182

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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.

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The Techsat-21 autonomous space science agent

Cited by 31 publications

References 5 publications

A day in an astronaut's life: reflections on advanced planning and scheduling technology

A day in an astronaut's life: reflections on advanced planning and scheduling technology

A Faster Algorithm for Checking the Dynamic Controllability of Simple Temporal Networks with Uncertainty

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

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