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Results for “autonomous Operations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Control systems for autonomous operation of the Magellan spacecraft

The Magellan low cost interplanetary mission spacecraft, scheduled for flight in 1989, employs a computer-based Attitude and Articulation Control System (AACS) that interfaces with spacecraft sensors and actuators. The sensors include two attitude reference units, a star-scanner unit, two digital sun sensors, and a tachometer. The actuators encompass three reaction wheels, a total of 12 attitude control thrusters, eight attitude-control engines, a solar array drive assembly, and an input-output drive assembly. A detailed account is given of the AACS's onboard computer architecture.

Huang, Whittak H.↗
NASA NTRS1993

Multi-beam range imager for autonomous operations

For space operations from the Space Station Freedom the real time range imager will be very valuable in terms of refuelling, docking as well as space exploration operations. For these applications as well as many other robotics and remote ranging applications, a small potable, power efficient, robust range imager capable of a few tens of km ranging with 10 cm accuracy is needed. The system developed is based on a well known pseudo-random modulation technique applied to a laser transmitter combined with a novel range resolution enhancement technique. In this technique, the transmitter is modulated by a relatively low frequency of an order of a few MHz to enhance the signal to noise ratio and to ease the stringent systems engineering requirements while accomplishing a very high resolution. The desired resolution cannot easily be attained by other conventional approaches. The engineering model of the system is being designed to obtain better than 10 cm range accuracy simply by implementing a high precision clock circuit. In this paper we present the principle of the pseudo-random noise (PN) lidar system and the results of the proof of experiment.

Marzwell, Neville I.↗
NASA NTRS2004

Online model-based diagnosis to support autonomous operation of an advanced life support system

This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed.

Non-NASA Center↗
NASA NTRS1996

TOPEX Electrical Power System - Autonomous Operation

The main objective of TOPEX/Poseidon Satellite is to monitor the world's oceans for scientific study of weather and climate prediction, coastal storm warning and maritime safety.

oceans climate predictions Electrical Power System↗
NASA NTRS2006

Sensor Data Qualification for Autonomous Operation of Space Systems

NASA's new Exploration initiative for both robotic and manned missions will require higher levels of reliability, autonomy and reconfiguration capability to make the missions safe, successful and affordable. Future systems will require diagnostic reasoning to assess the health of the system in order to maintain the system s functionality. The diagnostic reasoning and assessment will involve data qualification, fault detection, fault isolation and remediation control. A team of researchers at the NASA Glenn Research Center is currently working on a Sensor Data Qualification (SDQ) system that will support these critical evaluation processes, for both automated and human-in-the-loop applications. Data qualification is required as a first step so that critical safety and operational decisions are based on good data. The SDQ system would monitor a network of related sensors to determine the health of individual sensors within that network. Various diagnostic systems such as the Caution and Warning System would then use the sensor health information with confidence. The proposed SDQ technology will be demonstrated on a variety of subsystems that are relevant to NASA s Exploration systems, which currently include an electrical power system and a cryogenic fluid management system. The focus of this paper is the development and demonstration of a SDQ application for a prototype power distribution unit that is representative of a Crew Exploration Vehicle electrical power system; this provides a unique and relevant environment in which to demonstrate the feasibility of the SDQ technology.

Maul, William A.↗
NASA NTRS2003

An Approach to Autonomous Operations for Remote Mobile Robotic Exploration

This viewgraph presentation addresses the use of autonomy for remote mobile robotic exploration. The contents include; 1) Why Use Autonomy?; 2) What Are Some Options? JPL (Reasoning); 3) More Options.. . (Modeling); 4) The CLEaR Control System (Closed Loop Execution and Recovery); 5) Method of Response; 6) Overall Goal; 7) CLEaR in Action; 8) Initial Scenario; 9) Initial Scenario - Planned; 10) Unforeseen Events; and 11) Ongoing Research.

rovers↗
NASA NTRS2010

Onboard Run-Time Goal Selection for Autonomous Operations

We describe an efficient, online goal selection algorithm for use onboard spacecraft and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗
NASA NTRS2018

Auto-Gopher-II – A wireline rotary-hammer ultrasonic drill that operates autonomously

An important challenge of exploring the solar system is the ability to penetrate at great depths the subsurface of planetary bodies for sample collection. The requirements of the drilling system are minimal mass, volume and energy consumption. To address this challenge, a deep drill, called the Auto-Gopher II, is currently being developed as a joint effort between JPL’s NDEAA laboratory and Honeybee Robotics Corp. The Auto-Gopher II is a wireline rotaryhammer drill that combines breaking formations by hammering using a piezoelectric actuator and removing the cuttings by rotating a fluted bit. The hammering is produced by the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that has been developed by the JPL team as an adaptable tool for many drilling and coring applications. The USDC uses an intermediate free-flying mass to convert high frequency vibrations of a piezoelectric transducer horn tip into sonic hammering of the drill bit. The USDC concept was used in a previous task to develop an Ultrasonic/Sonic Ice Gopher and then integrated into a rotary hammer device to develop the Auto-Gopher-I. The lessons learned from these developments are being integrated into the development of the Auto-Gopher-II, an autonomous deep wireline drill with integrated cuttings and sample management and drive electronics. In this paper the latest development will be reviewed including the piezoelectric actuator, cuttings removal and retention flutes and drive electronics.

Paulsen, Gale L.↗
NASA NTRS2021

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.

Advanced avionics↗