Onboard autonomy software on the Three Corner Sat mission
This paper discusses the onboard autonomy software on the Three Corner Sat mission.
Engineering topics
Publications and source records attributed to Engelhardt, B..
This paper discusses the onboard autonomy software on the Three Corner Sat mission.
This paper talks about the techsat-21 autonomous sciencecraft constellation.
The paper talks about the planning, scheduling, and execution framework used in ASC (Autonomous Sciencecraft Constellation).
This paper introduces two benchmark problem sets based on actual space mission operations.
We examine four decision criteria that make varying assumptions about characteristics of the random variable.
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Three Corner Sat (3CS) is a mission of three university nanosatellites scheduled for launch on September 2002. The 3CS misison will utilize significan onboard autonomy to perform onboard science data validation and replanning.
This paper presents an overview of the intelligent decison-making capabilities of the CLARAty robotic architecture for autonomy.
We propose an explorer that uses a flexible problem-solver with a significant capacity to adapt its behavior.
This paper describes the mixed-initiative planning system for MAMM, which dramatically reduced mission-planning costs through automation to just a few scenarios for evaluating mission-design trades.
This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities.
The Autonomous Sciencecraft Constellation flight demonstration (ASC) will fly onboard the Air Forces's TechSat-21 constellation. Demonstration of its capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreadable without this technology.
Most approaches to robust automony with respect to planning and execution are focused on either providing models that allow for flexibility or providing techniques for changing models to improve performance. We take these techniques into consideration, but focus the majority of our work on robust autonomous planning and execution with imperfect models.
In this paper, we describe the three major areas for autonomous systems for space exploration: free-flying spacecraft, planetary rovers, and ground communications stations.
With adaptive problem solving, we take a biologically-inspired approach to both stochastic optimization and search in order to enable a spacecraft to adapt its environment-specific bevahior in-situ.
Optimization of expected values in a stochastic domain is common in real world applications.
Optimization of expected values in a stochastic domain is common in real world applications.
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