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A system of embedded sensors that can be incorporated into the wheel of any future mission rover would provide for a simple and fairly unobtrusive way to measure the distribution of electrostatic fields on the Martian surface and to measure variations in soil electrostatic response. This technology could perhaps be applied to different types of sensors that require the mobility provided by a rover s wheel.
The Portable Life Support System (PLSS) of the Exploration Extravehicular Mobility Unit (xEMU) requires sensors capable of measuring the major constituents of the gas stream. These major constituents include oxygen, carbon dioxide, and water vapor. The sensors must operate across a wide range of flow and pressure conditions and introduce very low pressure drop in the ventilation loop. The sensors must operate with low power and occupy a small volume. This paper reports the development of a compact, low power, multi-parameter astronaut life support sensor (M-PALSS). M-PALSS consists of an array of low-power chemical microsensors for oxygen, carbon dioxide, water vapor, and pressure. M-PALSS includes custom electronics to control the sensors and is packaged in a custom housing that meets the volume and shape requirements for service in the PLSS.
During this seminar, I will talk about three of the projects I’ve been involved with at NASA in the last few years: - The Human Exploration Research Analog (HERA) is a ground-based astronaut analog mission run at NASA’s JSC in Houston to study and evaluate impacts on the crew due to isolation, remoteness, and confined habitation. NASA scientists use the collected data to develop and verify countermeasures to reduce or mitigate psychological and physiological effects for future Deep Space missions. This simulation was a 45-day trip to Mars’s moon Phobos and back with the goal of performing geological operations with complete communications delays in effect. - Astrobee is a new class of free-flying robots that operates in the interior of the International Space Station (ISS). In addition to being a research platform for microgravity free-flying robotics, Astrobee improves the efficiency of ISS operations by providing flight and payload controllers with a mobile camera and a sensor platform. - NASA is developing new deployable structures and material technologies for solar sail propulsion systems destined for future low-cost deep space missions. NASA’s Advanced Composite Solar Sail System (ACS3) uses composite materials in its novel, lightweight booms that deploy from a Cubesat. Data obtained from ACS3 will guide the design of future larger-scale composite solar sail systems that could be used for several deep space exploration missions
The Portable Life Support System (PLSS) of the Exploration Extravehicular Mobility Unit (xEMU) requires sensors capable of measuring the major constituents of the gas stream. These major constituents include oxygen, carbon dioxide, and water vapor. The sensors must operate across a wide range of flow and pressure conditions and introduce very low pressure drop in the ventilation loop. The sensors must operate with low power and occupy a small volume. This paper reports the development of a compact, low power, multi-parameter astronaut life support sensor (M-PALSS). M-PALSS consists of an array of low-power chemical microsensors for oxygen, carbon dioxide, water vapor, and pressure. M-PALSS includes custom electronics to control the sensors and is packaged in a custom housing that meets the volume and shape requirements for service in the PLSS.
The Portable Life Support System (PLSS) of the Exploration Extravehicular Mobility Unit (xEMU) requires sensors capable of measuring the major constituents of the gas stream. These major constituents include oxygen, carbon dioxide, and water vapor. The sensors must operate across a wide range of flow and pressure conditions and introduce very low pressure drop in the ventilation loop. The sensors must operate with low power and occupy a small volume. This paper reports the development of a compact, low power, multi-parameter astronaut life support sensor (M-PALSS). M-PALSS consists of an array of low-power chemical microsensors for oxygen, carbon dioxide, water vapor, and pressure. M-PALSS includes custom electronics to control the sensors and is packaged in a custom housing that meets the volume and shape requirements for service in the PLSS.
Tracked mobile robots in the 20 kg size class are under development for applications in urban reconnaissance. For efficient deployment, it is desirable for teams of robots to be able to automatically execute path following behaviors, with one or more followers tracking the path taken by a leader. The key challenges to enabling such a capability are (l) to develop sensor packages for such small robots that can accurately determine the path of the leader and (2) to develop path following algorithms for the subsequent robots. To date, we have integrated gyros, accelerometers, compass/inclinometers, odometry, and differential GPS into an effective sensing package. This paper describes the sensor package, sensor processing algorithm, and path tracking algorithm we have developed for the leader/follower problem in small robots and shows the result of performance characterization of the system. We also document pragmatic lessons learned about design, construction, and electromagnetic interference issues particular to the performance of state sensors on small robots.
The data from the collimated sensors of the LEND instrument are shown to be of exceptionally high quality. Counting uncertainties are about 0.3% relative and are shown to be the only significant source of random error, thus conclusions based on small differences in count rates are valid. By comparison with the topography of Shoemaker crater, the spatial resolution of the instrument is shown to be consistent with the design value of 5 km for the radius of the circle over which half the counts from the lunar surface would be determined. The observed epithermal-neutron suppression factor due to the hydrogen deposit in Shoemaker crater of 0.25 plus or minus 0.04 cps is consistent with the collimated field-of-view rate of 1.7 cps estimated by Mitrofanov et al. (2010a). The statistical significance of the neutron suppressed regions (NSRs) relative to the larger surrounding polar region is demonstrated, and it is shown that they are not closely related to the permanently shadowed regions. There is a significant increase in H content in the polar regions independent of the H content of the NSRs. The non-NSR H content increases directly with latitude, and the rate of increase is virtually identical at both poles. There is little or no increase with latitude outside the polar region. Various mechanisms to explain this steep increase in the non-NSR polar H with latitude are investigated, and it is suggested that thermal volatilization is responsible for the increase because it is minimized at the low surface temperatures close to the poles.
The generation of waves by winds across Earth's water oceans is a topic of enduring fascination. However, the physics of the problem are rather forbidding and thus the relationships between real-world windspeed and sea state tend to be empirical. Such empirical relations are of limited utility in environments where the physical parameters are different, such as the surfaces of other planets. These environments have only recently come to oceanographers attention, with the discovery of ancient shorelines and lakes on Mars, and the prospects for and recent evidence of lakes and seas of liquid hydrocarbons on Saturn's moon Titan. We are aware of only one other published experimental wind-water tunnel study where the fluid parameters have been varied. This used artificially-generated mm-scale waves at 3.8-7.6 Hz in water, glycerol solutions (higher viscosity) and surfactant solutions (lower surface tension). Lower viscosity solutions had higher wave growth rates: surprisingly, higher surface tension led to more rapid wave growth. The liquid density was not appreciably varied, and 1 bar air was used throughout.We used the MARSWIT (Mars Wind Tunnel) operated by ASU at NASA Ames. A fiberglass tray (5 cm x 120 cm x 75 cm) was installed in the tunnel, with an approx. 1:5 ramp to prevent strong flow separation. The tray was filled to a depth of about 4 cm. Sensors were clamped to the tray itself or held by a steel and aluminium frame just above the water level. A towel was draped on the water surface at the downwind end of the tray to act as a damper to suppress wave reflection. Position-sensitive infrared (IR) reflection sensors (Sharp GP12D02) and ultrasonic rangers (Devantech DF-04) used in mobile robotics were used as water level sensors. The tray was observed with a video camera, whose output could be viewed on a monitor and recorded on VHS tape.
Solid-state lighting (SSL) technologies have penetrated the general illumination market in recent years, largely replacing conventional technologies such as incandescent and fluorescent lighting. Most of the initial excitement about light-emitting diode (LED) sources for SSL devices focused on their energy savings potential resulting from vast improvements in source efficiency and luminous efficacy compared with conventional illumination products. More recently, the focus has shifted toward other aspects of lighting application efficiency, namely intensity effectiveness and spectral efficiency, because of the ease of controlling both the light intensity of LEDs with drive voltage and the color properties of the LED-based illuminators. To capitalize on the energy savings of increased intensity effectiveness and spectral efficiency, a lighting control system (LCS) is often used. While the current penetration of LCSs is relatively modest, it is anticipated that lighting controls (i.e., connected lighting, controls and LED and conventional lighting) could have an installed penetration as higher as 46% by the year 2035, saving an additional 1.3 quads of energy. Despite the large energy savings that can be gained from using LCSs, standard test methods for evaluating sensors employed in LCSs and reliability data of the LCSs and their components are generally lacking. The National Electrical Manufacturers Association (NEMA) developed the only standard, NEMA WD 7-2011 (R2016), to test occupancy and motion sensor performance (herein referred to as “the NEMA protocol”). In a previous U.S. Department of Energy (DOE) effort, some concerns of the NEMA protocol were identified (e.g., strict height and weight limits on test subjects, large amounts of manual effort, sometimes inconsistent repeatability). During the current work, a consistent detection length test (DLT) and a Robotic Sensor Evaluation System (RoboSES) were developed to alleviate some of these concerns. RoboSES acts as a human surrogate by using thermal pads on a mannequin and a remote-controlled mobile base to test a sensor’s field of view (FOV). This report builds on the earlier DOE efforts to understand sensor technologies used in LCSs for general illumination. Specifically, this report describes the optimization of RoboSES, characterizes and establishes test methods to assess the reliability of multiple passive infrared (PIR) sensors, and reports the findings of robustness and reliability testing on two commercial PIR sensors intended for residential applications. The information presented in this report is gained from up to 4,000 hours (hrs) of accelerated stress tests (ASTs).
The performance of non-trivial tasks by a mobile robot has been a long term objective of robotic research. One of the major stumbling blocks to this goal is the conversion of the high-level planning goals and commands into the actuator and sensor processing controls. In order for a mobile robot to accomplish a non-trivial task, the task must be described in terms of primitive actions of the robot's actuators. Most non-trivial tasks require the robot to interact with its environment; thus necessitating coordination of sensor processing and actuator control to accomplish the task. The main contention is that the transformation from the high level description of the task to the primitive actions should be performed primarily at execution time, when knowledge about the environment can be obtained through sensors. It is proposed to produce the detailed plan of primitive actions by using a collection of low-level planning components that contain domain specific knowledge and knowledge about the available sensors, actuators, and sensor/actuator processing. This collection will perform signal and control processing as well as serve as a control interface between an actual mobile robot and a high-level planning system. Previous research has shown the usefulness of high-level planning systems to plan the coordination of activities such to achieve a goal, but none have been fully applied to actual mobile robots due to the complexity of interacting with sensors and actuators. This control interface is currently being implemented on a LABMATE mobile robot connected to a SUN workstation and will be developed such to enable the LABMATE to perform non-trivial, sensor-intensive tasks as specified by a planning system.
Methane (CH 4 ), an abundant greenhouse gas, is the second largest contributor to global warming after carbon dioxide (CO 2 ). In comparison to CO 2 , CH 4 has a larger warming effect over a much shorter lifetime. While technologies to radically reduce global carbon dioxide emissions are materializing, rapid reductions in methane emissions are needed to limit near-term warming. Methane is primarily emitted as a byproduct from agricultural activities and energy extraction/utilization and is currently monitored via bottom-up (i.e., activity level) or top-down (via airborne or satellite retrievals) approaches. However, significant methane leaks remain undetected, and emission rates are challenging to characterize with current monitoring frameworks. In this report, we study methane leaks from oil and gas infrastructure using a tiered monitoring approach that combines bottom-up and top-down approaches in an integrated framework. We describe the individual advantages of bottom-up and top-down sensors in both stationary and mobile settings before characterizing how a fully integrated framework can improve predictions and uncertainties of potential leak locations and their emission rates. Further, we study the impact of different atmospheric (wind) conditions on integrated methane monitoring and develop a probabilistic approach to optimal sensor placement, thereby shortening detection times and improving monitoring capabilities. Last, we discuss how biogenic flux modeling can be used to improve assessment of background methane concentrations needed to fully assess the sensitivity of a tiered monitoring system.
Background: Older adults spend a considerable amount of time inside their residences; however, most research investigates out-of-home mobility and its health correlates. We measured indoor mobility using room-to-room transitions, tested their psychometric properties, and correlated indoor mobility with cognitive and functional status. Materials and Methods: Community-dwelling older adults living alone ( n = 139; age = 78.1 ± 8.6 years) from the Oregon Center for Aging & Technology (ORCATECH) and Minority Aging Research Study (MARS) were included in the study. Two indoor mobility features were developed using non-parametric parameters (frequency; stability): Indoor mobility frequency (room-to-room transitions/day) was detected using passive infrared (PIR) motion sensors fixed on the walls in four geographic locations (bathroom; bedroom; kitchen; living room) and using door contact sensors attached to the egress door in the entrance. Indoor mobility stability was estimated by variances of number of room-to-room transitions over a week. Test-retest reliability (Intra-class coefficient, ICC) and the minimal clinically important difference (MCID) defined as the standard error of measurement (SEM) were generated. Generalized estimating equations models related mobility features with mild cognitive impairment (MCI) and functional status (gait speed). Results: An average of 206 days (±127) of sensor data were analyzed per individual. Indoor mobility frequency and stability showed good to excellent test-retest reliability (ICCs = 0.91[0.88–0.94]; 0.59[0.48–0.70]). The MCIDs of mobility frequency and mobility stability were 18 and 0.09, respectively. On average, a higher indoor mobility frequency was associated with faster gait speed (β = 0.53, p = 0.04), suggesting an increase of 5.3 room-to-room transitions per day was associated with an increase of 10 cm/s gait speed. A decrease in mobility stability was associated with MCI (β = −0.04, p = 0.03). Discussion: Mobility frequency and stability in the home are clinically meaningful and reliable features. Pervasive-sensing systems deployed in homes can objectively reveal cognitive and functional status in older adults who live alone.
These data were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI; https://www.arm.gov/research/campaigns/amf2018cacti ) field campaign in the Sierras de Córdoba mountain range of north-central Argentina as part of ARM Aerial Facility (AAF) deployment. The ARM Aerial Facility Gulfstream-1 was operated from Las Higueras Airport (IATA: RCU, ICAO: SAOC), Río Cuarto, Córdoba, Argentina, for the Intensive Observation Period (IOP) from Nov. 1 through Dec. 15, 2018. The G-1 aircraft performed 22 research flights over the first ARM Mobile Facility (AMF1) location in the Sierras de Córdoba mountain range to measure atmospheric state and turbulence, cloud water content and droplet size distributions, aerosol precursor gases, aerosol chemical composition and size distributions. The current data set presents Best Estimate Aerosol Size Distribution: a merged aerosol size distribution composed of the data from 5 sensors; three aerosol spectrometers: Scanning Mobility Particle Sizer (SMPS), Ultra-High Sensitivity Aerosol Spectrometer (UHSAS), and Passive Cavity Aerosol Spectrometer (PCASP); and two cloud probes: Cloud Aerosol Spectrometer (CAS) and Fast Cloud Droplet Probe (FCDP). The SMPS data were interpolated to 1 second from “native” time resolution of about 64 second to match all other probes.
The advent of spacecraft mobile robots-free-flyng sensor platforms and communications devices intended to accompany astronauts or remotely operate on space missions both inside and outside of a spacecraft-has demanded the development of a simple and effective navigation schema. One such system under exploration involves the use of a laser-camera arrangement to predict relative positioning of the mobile robot. By projecting laser beams from the robot, a 3D reference frame can be introduced. Thus, as the robot shifts in position, the position reference frame produced by the laser images is correspondingly altered. Using normalization and camera registration techniques presented in this paper, the relative translation and rotation of the robot in 3D are determined from these reference frame transformations.
This paper describes a new approach in semi-autonomous mobile robots. In this approach the robot has sufficient computerized intelligence to function autonomously under a certain set of conditions, while the local system is a cooperative decision making unit that combines human and machine intelligence. Communication is then allowed to take place in a common mode and in a common language. A number of exception-handling scenarios that were constructed as a result of experiments with actual sensor data collected from two mobile robots were presented.
A testbed has been developed for the study of sensor systems to be used in telerobotic operations. The program, conducted in conjunction with Johnson Space Center of NASA, addresses the navigational problems associated with target acquisition and rendezvous for teleoperated robotic work stations. The program will utilize a mobile platform which will support various sensor systems during their development and testing in an earth-based environment. The testbed has been developed in support of a program to develop sensor systems that will aid in rendezvous and docking operations to be conducted as a part of the space station program. A mobile platform has been used to permit testing of these components in a conventional laboratory environment with consequent savings in cost and complexity. The sensor systems, while representative of devices currently in use for robotic applications, are not considered prototypical of the ones that will be used in the final applications. The test program provided information that will support the design of system augmentations and will lead to a comprehensive test program for sensor development.
Teleautonomous guidance (TG), a technique for the remote guidance of fast mobile robots, has been developed and implemented. With TG, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This type of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. TG allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. TG is based on the virtual force field (VFF) method, which was developed earlier for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data (such as that produced by ultrasonic sensors) and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles.
An AdvancedExtravehicular Mobility Unit (EMU) is being developed and tested in house at JSC. Multiple programs over the last decade have contributed to the success thus far including the SBIR/STTR program.