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This paper presents on-going esearch in robotic ispeciton of space platforms. Three main area of investigation are discussed: machine-vision inspection techniques, an integrated sensor end-effector, and an orbital environment laboratory simulation.
On February 18th, 2021, the Mars 2020 entry system successfully delivered the Perserverance rover to the surface of Mars at Jezero Crater. The entry capsule carried a set of instrumentation installed on the heat shield and backshell, named the Mars 2020 Entry, Descent, and Landing Instrumentation. The instruments include pressure transducers, thermocouples, heat flux gauges, and radiometers to measure the aerodynamic and aerothermodynamic performance of the entry vehicle. Three of these sensors, a thermocouple plug, heat flux gauge, and a radiometer, are located in close proximity on the backshell. Each sensor is exposed to roughly the same environment, but measured these environments in different ways, each with its own set of modeling and measurement error complications. This paper develops a method for blending each of these measurements together in a single algorithm to produce estimates of the aerothermodynamic environments at that location on the backshell. The approach makes use of the Kalman filter methodology for solving state estimation problems. The filter has a predictor/corrector structure in which simplified process models are used to propagate the aeroheating states forward through time, which are then updated based on the measurement data. The method has been tested on simulated datasets.
A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.
VfOx, which stands for “Venus Oxygen Fugacity” is the DAVINCI mission’s Student Collaboration Experiment (SCE); a small single- objective sensor used to measure the partial pressure of molecular oxygen in Venus’ lower atmosphere. Through the mission timeline, VƒOx will be designed, fabricated, tested, operated, and results analyzed by undergraduate and graduate students mentored by the DAVINCI team in partnership with Johns Hopkins University and other institutions. The simple principal of VƒOx is a ceramic O 2 sensor derived from common applications, utilizing diffusion of O -2 ions between a standard (PdO) inside the sensor and the target atmosphere measured by a mW level voltage that depends directly on the standard/sample fO 2 ratio. A 60-day environmental test of a prototype design of the sensor was conducted at the Glenn Extreme Environment Rig (GEER) from August to October of 2022, in which VƒOx (Fig. 1) was placed inside the experimental chamber (Fig. 2) and brought to Venus surface temperature (460 °C) and pressure (92 bar) conditions, in a Venus like atmosphere (96.5% CO 2 , 3.5% N 2 ) that included trace gases like SO 2 , maintained by occasional “boosts” of extra gas during the experimental run.
The performance requirements for hydrogen detection in aerospace applications often exceed those of more traditional applications. In order to ascertain the applicability of existing hydrogen sensors to aerospace applications, a survey was conducted of commercially available point-contact hydrogen sensors, and their operation was analyzed. The operation of the majority of commercial hydrogen sensors falls into four main categories: catalytic combustion, electrochemical, semiconducting oxide sensors, and thermal conductivity detectors. The physical mechanism involved in hydrogen detection for each main category is discussed in detail. From an understanding of the detection mechanism, each category of sensor is evaluated for use in a variety of space and propulsion environments. In order to meet the needs of aerospace applications, the development of point-contact hydrogen sensors that are based on concepts beyond those used in commercial sensors is necessary.
Recently there has been a growth in the number of fiber optical sensors used for health monitoring in the hostile environment of commercial aircraft. Health monitoring to detect the onset of failure in structural systems from such causes as corrosion, stress corrosion cracking, and fatigue is a critical factor in safety as well in aircraft maintenance costs. This report presents an assessment of an analysis model of optical data networking architectures used for monitoring data signals among these optical sensors. Our model is focused on the design concept of the wavelength-division multiplexing (WDM) method since most of the optical sensors deployed in the aircraft for health monitoring typically operate in a wide spectrum of optical wavelengths from 710 to 1550 nm.
In-situ measurement of surface acoustic wave (SAW) resonators were used to characterize piezoelectric materials behavior in a nuclear reactor environment. Lithium niobate and aluminum nitride devices were tested up to 500°C temperature and 450 kW reactor power (1.9x10 12 n/cm 2 s). The resonant frequency responds to step changes in temperature and power. Materials’ response are inferred from the observed resonant frequency changes, in particular the kinetic behavior is used to determine mechanisms responsible for observed changes. The observed response is attributed to two mechanisms: temperature increase from gamma heating and accumulation of radiation-induced defects. Both of these mechanisms alter the physical properties of the piezoelectric materials, particularly the elastic constants. The demonstrated repeatability and reliability of SAW devices are attractive for sensor applications in extreme environments.
The objective is to develop thin-film thermocouples for Space Shuttle Main Engine (SSME) components. Thin-film thermocouples have been developed for aircraft gas turbine engines and are in use for temperature measurement on turbine blades to 1800 F. The technology established for aircraft gas turbine engines will be adapted to the materials and environment encountered in the SSME. Specific goals are to expand the existing in-house thin-film sensor technology and to test the survivability and durability of thin-film sensors in the SSME environment.
Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.
Human space missions have critical needs for monitoring and control for life support systems. These systems have monitoring needs that include feedback for closed loop processes and quality control for environmental factors. Sensors and monitoring technologies assure that the air environment and water supply for the astronaut crew habitat fall within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the more distant the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. The lifetime of the calibration, for some analytes, was as long as 24 months. We are working on a sensor array and new algorithms that will include sensor response time in the analysis. The preliminary array analysis for two analytes shows that the analysis time, of an event, can be dropped from 45 minutes to less than10 minutes and array training time can be cut substantially. We will describe the lifetime testing of an array and show lifetime data on individual sensors. This progress will lead to more rapid identification of analytes, and faster training time of the array.
A miniature, multi-channel, electronically scanned pressure measuring device uses electrostatically bonded silicon dies in a multielement array. These dies are bonded at specific sites on a glass, prepatterned substrate. Thermal data is multiplexed and recorded on each individual pressure measuring diaphragm. The device functions in a cryogenic environment without the need of heaters to keep the sensor at constant temperatures.
Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human-like reasoning schemes which may include as little as six elemental behaviors embodied in fourteen qualitative rules.
Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several types of environments such as urban, suburban, and rural. It is difficult to implement current state-of-the-art methods approved for automated approach and landing for AAM operations. However, existing technology and systems that use vision, IR, radar, and GPS methods provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS. This paper builds on previous work by incorporating high fidelity simulations with computer graphics rendering to demonstrate a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft's onboard navigation solution.
Three technology highlights from the Science Mission Directorate (SMD) Astrophysics Division, Biological and Physical Sciences Division, and Planetary Science Division are featured: a) A new class of X-ray detector with unprecedented energy resolution and array size could help transform our understanding of the cosmos through unparalleled vision into the otherwise invisible universe. b) An autonomous microfluidic culturing system with CubeSat heritage is teaming up with two state-of-the-art radiation detectors to measure how biology responds to the radiation and reduced gravity environment on the lunar surface. c) Several core technologies developed via the Hot Operating Temperature Technology (HOTTech) Program were recently tested in the Glenn Extreme Environment Rig (GEER), which simulates the conditions on the surface of Venus.
As fossil fuel supplies decline, hydrogen is quickly becoming an increasingly important fuel source. Currently hydrogen is the prime fuel of today's space vehicles (e.g., Space Shuttle) and featured as a fuel for some prototype vehicles such as the BMW seven series model. Hydrogen is a colorless, odorless gas with a 4% lower explosive limit which makes leak detection a priority. In an effort to support the use of hydrogen, a chemochromic (color changing) sensor was developed that is robust, simple to use, and does not require active operation. It can be made into a thin tape which can be conveniently used for leak detection at flanges, valves, or outlets. Chemochromic sensors can be either reversible or irreversible; however, irreversible chemochromic sensors will be analyzed in this report. The irreversible sensor is useful during hazardous operations when personnel cannot be present. To actively monitor leaks, testing of the irreversible sensor against environmental effects was completed and results indicated this material is suitable for outdoor use in the harsh beachside environment of Kennedy Space Center. The experiments in this report will give additional results to the environmental testing by adding solid rocket booster residue as a variable. The primary motivation for these experiments is to prepare the sensors for the launch pad environment at the Kennedy Space Center. In an effort to simulate the atmosphere at the pads before and after launch, the chemochromic sensors are exposed to solid rocket residue under various conditions.
Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several environments, such as urban, suburban, and rural. It is challenging to implement current state-of-the-art methods approved for automated approach and landing for AAM operations with challenges such as GPS degradation in urban environments and visual navigation aids like the glideslope and localizer being narrow and not allowing alternative incoming landing angles at vertiports. However, existing technology and systems, i.e., the instrument landing system (ILS) with glideslope and localizer indicators that use vision, IR, radar, or GPS methods, provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations about heliport design (FAA AC 150/5390-2C), which is one of the closest references for vertiport requirements and regulations. The coplanar pose from orthography and scaling with iterations (COPOSIT) algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a vision-based approach and landing (VAL) sensor fusion navigation solution for GPS-denied environments. The VAL navigation solution provides promising simulation results for AAM PALS with Hough circle detection and feature correspondence, which demonstrate robustness to false positives. This paper incorporates moderately high- fidelity simulations with computer graphics rendering to show a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft’s onboard vision-based navigation solution.
There is a need to more thoroughly characterize the hostile space shuttle main engine (SSME) turbopump environment. It has been estimated that component surface heat flux in the hot-gas environment is about 10 MW/square meter, and this is about 50 times that encountered in aircraft engines. Also, material temperature transients can be as high as 1000 K in about 1 second. These transients can cause durability problems such as material cracking. Heat flux sensors placed in the turbopump components can partially characterize this environment by measuring surface heat flux. These heat flux data can be used to verify analytical-stress, boundary-layer, and heat-transfer design models. Preliminary plans were discussed at the first SSME durablity conference for designing and fabricating a new facility for the calibration and durability testing of prototype heat flux sensors for the SSME. This facility, which is necessary for assessment of new heat flux gauge concepts needed in the hostile SSME turbopump environment, is described.
Accurate quantification of combustor pressure dynamics for the primary purpose of experimental validation of computational fluid dynamics (CFD) codes requires the use of robust, reliable and sensitive pressure sensors that can resolve sub--pound-per-square-inch pressure levels in high temperature environments (i.e., combustor). The state of the art microfabricated piezoresistive silicon carbide (SiC) pressure sensors that we have developed are capable of operating reliably at 600 degrees Centigrade. This technology was used in support of the ARMD ISRP-ERA (NASA's Aeronautics Research Mission Directorate, Integrated System Research Project - Environmentally Responsible Aviation) program to quantify combustor thermoacoustic instabilities. The results showed that while the SiC pressure sensors survived the high temperature and measured instabilities, the diaphragm (force collector) was not thin enough to be sensitive in resolving sub-pound-per-square-inch pressures; 30 meters is the thinnest diaphragm achievable with conventional reactive ion etching (RIE) processes. Therefore, this precludes its use for sub-pound-per-square-inch pressure measurement with high fidelity. In order to effectively resolve sub-pound-per-square-inch pressures, a thinner more sensitive diaphragm (10 meters) is needed. To achieve this would require a new and innovative fabrication process technique.