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Chien, Steve A.

Publications and source records attributed to Chien, Steve A..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Romie: A Domain-Independent Tool for Computer-Aided Robust Operations Management

Romie is a decision support tool based on AI's latest advances in the domain of robust scheduling. Unlike all its predecessors, the tool allows to (i) visually model the operational problem and context entirely (ii) optimize to find near-optimal schedules while taking uncertainty into account and deals with (iii) a combination of various {key performance indicators (KPIs). It comes with a web user interface. Part or all of the modelled activities may be associated to random variables describing their stochastic durations, in order to produce schedules that are robust w.r.t. temporal uncertainty. Hence, depending on the pursued KPIs, the schedules maximize a combination of the following terms: the probability of satisfying the problem constraints, the expected return/efficiency, the expected outcome quality, and even the operators' wellness by minimizing its expected extra-hours. Initially developed for spatial exploration and demonstration in the context of Mars analog missions, this versatile tool is here applied to operations management in both biotechnology manufacturing and robots parametrization in a cave exploration context.

Chien, Steve A.↗
NASA NTRS2021

Lila: Optimal Dispatching in Probabilistic Temporal Networks using Monte Carlo Tree Search

Executing a Probabilistic Simple Temporal Network (PSTN) amounts at scheduling, i.e. \textit{dispatch}, a set of events under time uncertainty. This constitutes a NP-hard online optimization problem. The right execution time must be dynamically assigned to each event of the PSTN such that the temporal constraints are met, whereas activity durations are progressively observed as the execution unfolds. We propose a dispatching algorithm based on Monte Carlo Tree Search, called Lila, with the following characteristics: (i) it is an anytime algorithm, both offline and online, proven asymptotically optimal; (ii) it returns the current probability of success, either before or at any moment during operations; (iii) it handles any possible continuous or discrete, even non-parametric, probability distributions, as well as inter-dependencies between random variables, exogenous and endogenous uncertainty; and (iv) can be easily extended to handle probabilistic external events, PSTNs with resources, PSTNs with cutoff times and precondition chains, etc. Lila is universal in the sense that it can handle any dispatching protocol, simply by specifying it to the algorithm. It has the unlimited flexibility offered by the simulation paradigm, whilst it asymptotically converges to optimal decisions and/or robustness approximations.

Chien, Steve A.↗
NASA NTRS2020

Using Flexible Execution, Replanning, and Model Parameter Updates to Address Environmental Uncertainty for a Planetary Lander

When planning in unknown environments, a planner must ensure robustness to unknown phenomena and manage unpredictable variation in execution. Productivity in the face of these challenges requires an integrated approach to planning and execution that is capable of reacting to variation while still maximizing overall utility. We examine this problem in the context of the Europa Lander mission concept. We propose a planning and execution framework that responds to feedback using three techniques: (1) flexible execution, (2) periodic replanning, and (3) online model parameter and utility updates. The efficacy of each of these techniques is examined through simulation of the Europa Lander concept, showing higher utility achievement compared to baseline approaches.

Chien, Steve A.↗
NASA NTRS2017

Satellite Constellation Orbit Design to Enable a Space-Based Radio Interferometer

Two different design methods for a networked constellation of N small satellites are presented. In the first method, the (linear) Clohessy-Wilthsire equations are used as an initial design tool, followed by conversion to a two-body model. Discrepancies between the linear and nonlinear solutions are minimized in the conversion process. The second method utilizes invariant manifold theory, by perturbing a reference trajectory in different directions along the center eigenvectors. Both methods require 5N parameters to fully define a constellation. In a relative, rotating frame of the reference path, the spacecraft appear as periodic ellipses of varying sizes. Deployment, reconfiguration using propulsive maneuvers, and station keeping costs for an example mission scenario are addressed.

Chien, Steve A.↗
NASA NTRS2013

Automating Hyperspectral Data for Rapid Response in Volcanic Emergencies

In a volcanic emergency, time is of the essence. It is vital to quantify eruption parameters (thermal emission, effusion rate, location of activity) and distribute this information as quickly as possible to decision-makers in order to enable effective evaluation of eruption-related risk and hazard. The goal of this work was to automate and streamline processing of spacecraft hyperspectral data, automate product generation, and automate distribution of products. Visible and Short-Wave Infrared Images of volcanic eruption in Iceland in May 2010." class="caption" align="right">The software rapidly processes hyperspectral data, correcting for incident sunlight where necessary, and atmospheric transmission; detects thermally anomalous pixels; fits data with model black-body thermal emission spectra to determine radiant flux; calculates atmospheric convection thermal removal; and then calculates total heat loss. From these results, an estimation of effusion rate is made. Maps are generated of thermal emission and location (see figure). Products are posted online, and relevant parties notified. Effusion rate data are added to historical record and plotted to identify spikes in activity for persistently active eruptions. The entire process from start to end is autonomous. Future spacecraft, especially those in deep space, can react to detection of transient processes without the need to communicate with Earth, thus increasing science return. Terrestrially, this removes the need for human intervention.

Davies, Ashley G.↗
NASA NTRS2013

Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing

A set of automated planning algorithms is the current operations baseline approach for the Intelligent Payload Module (IPM) of the proposed Hyper spectral Infrared Imager (HyspIRI) mission. For this operations concept, there are only local (e.g. non-depletable) operations constraints, such as real-time downlink and onboard memory, and the forward sweeping algorithm is optimal for determining which science products should be generated onboard and on ground based on geographical overflights, science priorities, alerts, requests, and onboard and ground processing constraints. This automated planning approach was developed for the HyspIRI IPM concept. The HyspIRI IPM is proposed to use an X-band Direct Broadcast (DB) capability that would enable data to be delivered to ground stations virtually as it is acquired. However, the HyspIRI VSWIR and TIR instruments will produce approximately 1 Gbps data, while the DB capability is 15 Mbps for a approx. =60X oversubscription. In order to address this mismatch, this innovation determines which data to downlink based on both the type of surface the spacecraft is overflying, and the onboard processing of data to detect events. For example, when the spacecraft is overflying Polar Regions, it might downlink a snow/ice product. Additionally, the onboard software will search for thermal signatures indicative of a volcanic event or wild fire and downlink summary information (extent, spectra) when detected, thereby reducing data volume. The planning system described above automatically generated the IPM mission plan based on requested products, the overflight regions, and available resources.

Chien, Steve A.↗
NASA NTRS2013

Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing

A generic software framework analyzes data from broad coverage sweeps or general larger areas of interest. Change detection methods are used to extract subsets of directed swath areas that intersect areas of change. These areas are prioritized and allocated to targetable assets. This method is deployed in an automatic fashion, and has operated without human monitoring or intervention for sustained periods of time (months).

Chien, Steve A.↗