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Chien, S.

Publications and source records attributed to Chien, S..

At least 19 records

Ground-Based Automated Scheduling for the Mars 2020 Rover

The Mars 2020 Rover Mission will be using an automated ground-based scheduling system called Copilot to schedule the rover’s activities at landing. Using automated scheduling technology will allow for plans to be generated more quickly. Because automated scheduling tools have not been widely used for prior rover missions, developing users’ trust in the system is crucial. An explainable scheduling tool called Crosscheck has been developed to visualize the creation of a schedule, and to explain why activities failed to schedule given their constraints. This will allow science planners to change activity constraints to allow failed activities to successfully schedule, achieving their science goals.

Towey, S.

Adaptive, Model-Driven Observation for Earth Science

In this article we introduce a preliminary effort to apply an adaptive and model-driven sensing framework to the study of large scale storms. Such systems pose great challenges as studying complex, fast developing Earth science phenomena such as hurricanes have significant spatial extent and complex temporal evolution making comprehensive sensing of the entire phenomena prohibitive. We use adaptive sensing to direct sensing in an autonomous and intelligent cycle. We show how online analysis would increase the knowledge of the event and decrease uncertainty in predictions.

Swope, J.

Onboard Automated Scheduling for the Mars 2020 Rover

The Mars 2020 Mission, scheduled to land on Mars February 18, 2021, has developed an onboard scheduling system [1]. The rationale for the onboard scheduler is to enable the Perseverance rover to adjust its activities in response to activities taking longer or shorter than planned, or using more or less resources than expected, as effectively using these resources could significantly improve rover productivity [2]. If deployed, the onboard scheduler would be an unprecedented use of Artificial Intelligence/Autonomy onboard software in a key role for a major mission.

Biehl, J.

Towards an Autonomous Space In-Situ Marine Sensorweb

We describe ongoing efforts to integrate and coordinate space and marine assets to enable autonomous response to dynamic ocean phenomena such as algal blooms, eddies, and currents. Thus far we have focused on the use of remote sensing assets (e.g. satellites) but future plans include expansions to use a range of in-situ sensors such as gliders, autonomous underwater vehicles, and buoys/moorings.

Chien, S.

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Ip, Felipe

Central Avra Valley Storage and Recovery Project (CAVSARP) Site, Tucson, Arizona: Floodwater and Soil Moisture Investigations with Extraterrestrial Applications

Planetary geologists, geomorphologists, and hydrologists have hypothesized that Mars is a dynamic, water-enriched planet since the Mariner and Viking missions based on geologic, geomorphic, and topographic information. Recent acquisition of Gamma Ray and Neutron Spectrometer information has added further credence to this hypothesis. A unique investigation is underway to work towards being able to successfully map the extent and depth of water on Mars. Researchers from the University of Arizona and members of the Autonomous Sciencecraft Experiment (ASE) have been compiling multiple layers of information in time and space at the Central Avra Valley Storage and Recovery Project (CAVSARP) site, Tucson, Arizona, for eventual comparative analysis. This information has been acquired from a variety of observational/scientific platforms in controlled conditions. CAVSARP facility:

Rucker, D. F.

ASE Floodwater Classifier Development for EO-1 Hyperion Imagery

The objective of this investigation is to develop a prototype floodwater detection algorithm for Hyperion imagery. It will be run autonomously onboard the EO-1 spacecraft under the Autonomous Sciencecraft Experiment (ASE). This effort resulted in the development of two classifiers for floodwater, one of several classifier types that have been developed and will be uploaded to EO-1 in early 2004 in order to detect change related to transient processes such as volcanism, flooding, and ice formation and retreat.

Ip, Felipe

Autonomous Sciencecraft Experiment (ASE) Operations on EO-1 in 2004

The Autonomous Sciencecraft Experiment (ASE) has been selected for flight demonstration by NASAs New Millennium Program (NMP) as part of the Space Technology 6 (ST6) mission. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control software, image formation software, and science processing software will be uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 to detect surface modification related to volcanism, ice formation and retreat, and flooding.

Davies, A. G.