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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Ono, Masahiro↗
NASA NTRS2012

Joint Chance-Constrained Dynamic Programming

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Ono, Masahiro↗
NASA NTRS2008

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

autonomuys vehicles↗
NASA NTRS1996

A Framework for the Optimization of Discrete-Event Simulation Models

With the growing use of computer modeling and simulation, in all aspects of engineering, the scope of traditional optimization has to be extended to include simulation models. Some unique aspects have to be addressed while optimizing via stochastic simulation models. The optimization procedure has to explicitly account for the randomness inherent in the stochastic measures predicted by the model. This paper outlines a general purpose framework for optimization of terminating discrete-event simulation models. The methodology combines a chance constraint approach for problem formulation, together with standard statistical estimation and analyses techniques. The applicability of the optimization framework is illustrated by minimizing the operation and support resources of a launch vehicle, through a simulation model.

Joshi, B. D.↗
NASA NTRS2011

Chance-Constrained Guidance With Non-Convex Constraints

Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of failure) is below a user-specified bound known as the risk bound. An example problem is to drive a car to a destination as fast as possible while limiting the probability of an accident to 10(exp -7). This framework allows users to trade conservatism against performance by choosing the risk bound. The more risk the user accepts, the better performance they can expect.

FROM↗
NASA NTRS2011

NASA Tech Briefs, June 2011

Topics covered include: Wind and Temperature Spectrometry of the Upper Atmosphere in Low-Earth Orbit; Health Monitor for Multitasking, Safety-Critical, Real-Time Software; Stereo Imaging Miniature Endoscope; Early Oscillation Detection Technique for Hybrid DC/DC Converters; Parallel Wavefront Analysis for a 4D Interferometer; Schottky Heterodyne Receivers With Full Waveguide Bandwidth; Carbon Nanofiber-Based, High-Frequency, High-Q, Miniaturized Mechanical Resonators; Ultracapacitor-Based Uninterrupted Power Supply System; Coaxial Cables for Martian Extreme Temperature Environments; Using Spare Logic Resources To Create Dynamic Test Points; Autonomous Coordination of Science Observations Using Multiple Spacecraft; Autonomous Phase Retrieval Calibration; EOS MLS Level 1B Data Processing Software, Version 3; Cassini Tour Atlas Automated Generation; Software Development Standard Processes (SDSP); Graphite Composite Panel Polishing Fixture; Material Gradients in Oxygen System Components Improve Safety; Ridge Waveguide Structures in Magnesium-Doped Lithium Niobate; Modifying Matrix Materials to Increase Wetting and Adhesion; Lightweight Magnetic Cooler With a Reversible Circulator; The Invasive Species Forecasting System; Method for Cleanly and Precisely Breaking Off a Rock Core Using a Radial Compressive Force; Praying Mantis Bending Core Breakoff and Retention Mechanism; Scoring Dawg Core Breakoff and Retention Mechanism; Rolling-Tooth Core Breakoff and Retention Mechanism; Vibration Isolation and Stabilization System for Spacecraft Exercise Treadmill Devices; Microgravity-Enhanced Stem Cell Selection; Diagnosis and Treatment of Neurological Disorders by Millimeter-Wave Stimulation; Passive Vaporizing Heat Sink; Remote Sensing and Quantization of Analog Sensors; Phase Retrieval for Radio Telescope and Antenna Control; Helium-Cooled Black Shroud for Subscale Cryogenic Testing; Receive Mode Analysis and Design of Microstrip Reflectarrays; and Chance-Constrained Guidance With Non-Convex Constraints.

Source record↗
NASA NTRSDate not supplied

Strategy for Maturing Active Radiation Shielding Concepts

Active shielding strategies for protecting astronauts on exploration missions has long been a dream that proved evasive. Study after study since the early 1970’s has shown that solutions are both mass and power prohibitive. This talk will give an overview of current NASA work aimed at making advancements in the area of active shielding. The basic project premise is that we may have a better chance at success if we: (1) remove the constraint of having to reduce the exposure to zero, and instead focus on how to increase the number of ‘safe’ days in space according to the current NASA risk posture; (2) sub-divide the proton and heavy ion energy spectrum to identify a starting point in energy that may yield a non-negligible reduction in ion flux at power levels achievable with current technology, and; (3) develop methods to use scaling to build, test and mature small-scale shielding structures on the ground as a pathway to identifying technology development investment strategies. A top-level overview of these strategies will be presented during this talk.

Radiation Protection↗
NASA NTRS2010

LCROSS: A High Return, Small Satellite Mission

Early in 2006, the NASA Exploration Systems Mission Directorate (ESMD) held a competition for NASA Centers to propose innovative ideas for a secondary payload mission to launch with the Lunar Reconnaissance Orbiter (LRO) to the Moon. The successful proposal could cost no more than $80 million dollars (less was preferred), would have to be ready to launch with the LRO in 31 months, could weigh no more than 1000 kg (fuelled), and would be designated a risk-tolerant "Class D" mission. In effect, NASA was offering a fixed-price contract to the winning NASA team to stay within a cost and schedule cap by accepting an unusually elevated risk position. To address this Announcement of Opportunity to develop a cost-and-schedule-capped secondary payload mission to fly with LRO, NASA Ames Research Center (ARC) in Moffett Field, CA, USA embarked on a brainstorming effort termed "Blue Ice" in which a small team was asked to explore a number of mission scenarios that might have a good chance for success and still fit within the stated programmatic constraints. From this work, ARC developed and submitted six of the nineteen mission proposals received by ESMD from throughout the Agency, one of which was LCROSS - a collaborative effort between ARC and its industrial partner, Northrop-Grumman (NG) in Redondo Beach, CA, USA.

Andrews, Daniel R.↗
NASA NTRS2020

Contributions of Antarctic Meteorites in Understanding the Inner Solar System: The Interplay of Samples and Paradigms

Antarctic meteorites number nearly 50,000 in world collections, and have provided significant contributions to our understanding of the Solar System. Collections include samples from the Moon, Mars, asteroid 4 Vesta, as well as dozens or even hundreds of other bodies from the asteroid belt or near Earth objects. This 50th anniversary of the Japanese Antarctic finds from Yamato Mountains offers a chance to reflect on the contributions to planetary science. Antarctic meteorites have provided fundamental constraints on Solar System science in three major roles: A) unique samples of bodies (Mars and Vesta), B) complementary samples of bodies (Moon, together with Apollo and Luna), and C) foundational samples that have expanded the variety of known and documented materials in our sample collections. These have all contributed to the ideas and paradigms that have influenced the understanding of our Solar System.

Righter, K.↗
NASA NTRS2016

Computational Modeling to Limit the Impact Displays and Indicator Lights Have on Habitable Volume Operational Lighting Constraints

The goal of this investigation is to determine design limitations and architectural solutions that limit the impact light from displays and indicator lamps have on the operational environment task lighting and lighting countermeasure spectrum constraints. It is concerning that this innovative architectural lighting system, could be compromised by spectrums from display systems, architectural materials, and structures that are not considered as part a full system design implementation. The introduction of many Commercial Off the Shelf (COTS) products to the spacecraft volume that contain LEDs, without consideration to the human factors and biological constraints, is another problem. Displays and indicators are a necessary part of the spacecraft and it is the goal of this research project to determine constraints and solutions that allow these systems to be integrated while minimizing how the lighting environment is modified by them. Due to the potentially broad scope of this endeavor, the project team developed constraints for the evaluation. The evaluation will be on a set of tasks that required significant exposure in the same environment while having a large chance of impacting the light spectrum the crew is expected to receive from the architectural lighting system. The team plans to use recent HRP research on "Net Habitable Volume" [1] to provide the boundary conditions for volume size. A Zemax ® lighting model was developed of a small enclosure that had high intensity overhead lighting and a standard intensity display with LED indicator arrays. The computer model demonstrated a work surface illuminated at a high level by the overhead light source compared to displays and indicators whose light is parallel to the work plane. The overhead lighting oversaturated spectral contributions from the display and indicator at the task work surface. Interestingly, when the observer looked at the displays and LEDs within the small enclosure, their spectral contribution was significant but could be reduced by reflecting overhead light from the wall(s) to the observer. Direct observation of displays and LEDs are an issue because the user's viewing area is a display, not an illuminated work surface. Since avionics command centers consume significant crew time, the tasks that seemed at higher risk for unwanted spectral contributions as an operational volume with significant quantity of displays and indicators that were either under direct observation of the crew or impacting a volume the crew may be required to sleep in.

Clark, T. E.↗
NASA NTRS2013

Mixed-Strategy Chance Constrained Optimal Control

This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.

Ono, Masahiro↗
NASA NTRS2014

A Guideline for the Management of Renal Stones in Astronauts

There are no specific guidelines for the management of renal stones in astronauts. Given the increased risk for bone loss, hypercalcuria, and stone formation due to microgravity, a clinical practice guideline is needed. Methods An extensive review of the literature and current aeromedical standards for the management of renal stones was done. The NASA Flight Medicine Clinic's electronic medical record and Longitudinal Survey of Astronaut Health were also reviewed. This information was used to create an algorithm for the management of renal stones in astronauts. Results Guidelines are proposed based on accepted standards of care, with consideration to the environment of spaceflight. In a usual medical setting, asymptomatic, small stones less than 7 mm are often observed over time. Given the constraints of schedule, and the risks to crew health and mission, this approach is too liberal. An upper limit of 3 mm stone diameter was adopted before requiring intervention, because this is the largest size that has a significant chance of spontaneous passage on its own. Other specific guidelines were also created. Discussion The spaceflight environment requires more aggressive treatment than would otherwise be found with the usual practice of medicine. A small stone can become a major problem because it may ultimately require medical evacuation from orbit. Thus renal stones are a significant mission threat and should be managed in a systematic way to mitigate risks to crew health and mission success.

Reyes, David↗
NASA NTRS1974

A Markovian model for assessment of personnel hiring plans

As a result of the current economic environment, many organizations are having to operate with fewer resources. In the manpower area, these constraints have forced organizations to operate within well-defined hiring plans. Exceeding personnel ceilings is in most cases an intolerable situation. A mathematical model, based on the theory of Markov processes, is presented which can be used to assess the chances of success of personnel hiring plans. The model considers a plan to be successful if the final population size, at the end of the planning period, lies within a range specified by management. Although this model was developed to assess personnel hiring plans at the Goddard Space Flight Center, it is directly applicable wherever personnel hiring plans are used.

Katz, L. G.↗
NASA NTRS2022

Chance-Constrained System Identification of Nonlinear Discrete Systems with Safety and Stability Guarantees

This paper presents a discrete-time nonlinear system identification method while satisfying the stability and safety properties of the system with high probability. An Extreme Learning Machine (ELM) is used with a Gaussian assumption on the function reconstruction error. A quadratically constrained quadratic program (QCQP) is developed with probabilistic safety and stability constraints that are only required to be satisfied at sampled points inside the invariant region. The proposed method is validated using two simulation examples: a two degrees-of-freedom (DoF) robot manipulator with constraints on joint angles whose trajectories are guaranteed to remain inside a safe set and on motion trajectories data of a hand-drawn shape.

Iman Salehi↗
NASA NTRS2022

Formal Methods for Trusted Space Autonomy, Boon or Bane?

Trusted Space Autonomy is challenging in that space systems are complex artifacts deployed in a high stakes environment with complicated operational settings. Thus far these challenges have been met using the full arsenal of tools: formal methods, informal methods, testing, runtime techniques, and operations processes. Using examples from previous deployments of autonomy to the Remote Agent on DS-1, Autonomous Sciencecraft on EO-1, WATCH on MER, IPEX, AEGIS on MER, MSL, and M2020, and the M2020 Onboard planner, we discuss how each of these approaches have been used to enable successful deployment of autonomy. We next focus on relatively limited use of formal methods (both prior to deployment and runtime methods). From the needs perspective, formal methods represent the best chance for reliable autonomy as testing, informal methods, and operations accommodations do not scale well with increasing complexity of the autonomous system. However from the practice perspective, formal methods have been limited in their application due to difficulty in eliciting formal specifications and challenges in representing complex constraints such as metric time and resources. We discuss some of these challenges as well as the opportunity to extend formal and informal methods into runtime validation systems.

Chien, Steve↗
NASA NTRS1995

The faint X-ray sources in and out of omega Centauri: X-ray observations and optical identifications

We present the results of an observation of the globular cluster omega Cen (NGC 5139) with the Einstein high-resolution imager (HRI). Of the five low-luminosity X-ray sources toward omega Cen which were first identified with the Einstein imaging proportional counter (IPC) (Hertz and Grindlay 1983a, b), two are detected in the Einstein HRI observation: IPC sources A and D. These detections provide source positions accurate to 3 sec-4 sec; the positions are confirmed in a ROSAT HRI observation reported here. Using CCD photometry and spectroscopy, we have identified both sources as foreground dwarf M stars with emission lines (dMe). The chance projection of two Mde stars within approximately 13 min of the center of omega Cen is not extraordinary, given the space density of these stellar coronal X-ray sources. We discuss the possible nature of the three as yet unidentified IPC sources toward omega Cen, and consider the constraints that the Einstein observations place on the total population of X-ray sources in this cluster. The integrated luminosity from faint X-ray sources in omega Cen appears to be low relative to both the old open cluster M67 and the post-core-collapse globular, NGC 6397.

Cool, Adrienne M.↗