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The earth as viewed from space in visible light at night reveals some features not easily discernible during the day such as aurora, forest fires, city lights and gas flares. In addition, those features having a high albedo such as snow and ice can be identified on many moonlit nights nearly as well as they can in sunlight. The Air Force DMSP satellites have been operating in the visible wavelengths at night since the mid 1960s. Most all other satellites having optical sensors are incapable of imaging at night. Imaging systems having improved light sensitivity in the visible portion of the spectrum should be considered when planning future earth resources satellite missions in order to utilize nighttime as well as daytime visual observations.
An improved predictive understanding of the integrated Earth system, including human interactions, will provide direct benefits by anticipating and planning for possible impacts on commerce, agriculture, energy, resource utilization, human safety, and environmental quality. The central goal of the U.S. Global Change Research Program (USGCRP) is to help establish the scientific understanding and the basis for national and international policymaking related to natural and human-induced changes in the global Earth system. This will be accomplished through: (1) establishing an integrated, comprehensive, long-term program of documenting the Earth system on a global scale; (2) conducting a program of focused studies to improve our understanding of the physical, geological, chemical, biological, and social processes that influence the Earth system processes; and (3) developing integrated conceptual and predictive Earth system models.
1. Habitat Structures at MSFC is one element of the In-Situ Fabrication and Repair (ISFR) Program: ISFR develops technologies for fabrication, repair and recycling of tools, parts, and habitats/structures using in-situ resources. ISRU - based habitat structures are considered Class III. 2. Habitat Structure Purpose: Develop Lunar and/or Martian habitat structures for manned missions that maximize the use of in-situ resources to address the following agency topics: bioastronautics critical path roadmap; strategic technical challenges defined in H&RT formulation plan: margins and redundancy; modularity, robotic network, space resource utilization; autonomy, affordable logistics pre-positioning.
The careful planning, optimized utilization, and responsive disposition of processes, personnel, resources, and real and personal property, focused upon leveraging existing Shuttle and ISS assets for Exploration programs safety and mission success.
New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.
The Resource Prospector (RP) is an In-‐Situ Resource Utilization (ISRU) lunar rover mission under study by NASA. RP is planned to launch in 2020 to prospect for subsurface volatiles and to extract oxygen from lunar regolith. The mission will address several of NASA's "Strategic Knowledge Gaps" for lunar exploration. The mission will also address the Global Exploration Roadmap's strategic goal of using local resources for human exploration. The distribution of lunar subsurface volatiles drives the mission requirement for mobility. The spatial distribution is hypothesized to be governed by impact cratering with the top 0.5 m being patchy at scales of 100 m. The mixing time scale increases with depth (less frequent larger impacts). Consequently, increased mobility reduces the depth requirement for sampling. The target RP traverse will extend 1 km radially from the landing site to sample craters of varying sizes. Sampling craters with different ages will reveal possible volatile emplacement history. In 1 Ga, approximately 60-70 craters of 10 m diameter form per km2. Thus, the rover will need to sample at least ten of these craters, which may require a total traverse path length of 2-‐3 km. During 2014-2015, we developed an initial prototype rover for RP. The current design is a solar powered, four-wheeled vehicle, with hub motor drive, offset four wheel steering, and active suspension. Active suspension provides capabilities including changing vehicle ride height, traversing comparatively large obstacles, and controlling load on the wheels. All-wheel steering enables the vehicle to point arbitrarily while roving, e.g., to keep the solar array pointed at the sun while in motion. The offset steering combined with active suspension improves driving in soft soil. The rover's on-board software utilizes NASA's Core Flight Software, which is a reusable flight software environment. During 2015, we completed the initial rover software build, which provides low-level hardware interfaces, basic mobility control, waypoint driving, odometry, basic error checking, and camera services. Development of the prototype rover has enabled maturation of many of the subsystems to TRL 5. During the next year, we will conduct integrated testing of concepts of operation, navigation, and remote driving tools. In addition, we will perform environmental tests including radiation (avionics), thermal and thermal/vacuum (mechanisms), and gravity offload (mobility).
The primary objectives of the Payload Crew Activity Planning Integration task were to: (1) Determine feasible, cost-effective payload crew activity planning integration methods. (2) Develop an implementation plan and guidelines for payload crew activity plan (CAP) integration between the JSC Orbiter planners and the Payload Centers. Subtask objectives and study activities were defined as: (1) Determine Crew Activity Planning Interfaces. (2) Determine Crew Activity Plan Type and Content. (3) Evaluate Automated Scheduling Tools. (4) Develop a draft Implementation Plan for Crew Activity Planning Integration. The basic guidelines were to develop a plan applicable to the Shuttle operations timeframe, utilize existing center resources and expertise as much as possible, and minimize unnecessary data exchange not directly productive in the development of the end-product timelines.
Recently, many expert systems were developed in a LISP environment and then ported to the real world C environment before the final system is delivered. This situation may require that the entire system be completely rewritten in C and may actually result in a system which is put together as quickly as possible with little regard for maintainability and further evolution. With the introduction of high performance UNIX and X-windows based workstations, a great deal of the advantages of developing a first system in the LISP environment have become questionable. A C-based AI development effort is described which is based on a software tools approach with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching and a blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May 1987 and will be used for operations scheduling of the Explorer Platform in November 1991.
A C-based artificial intelligence (AI) development effort which is based on a software tools approach is discussed with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching, and blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) Shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May of 1987 and will be used for operations scheduling of the Explorer Platform in Nov. of 1991.
The purpose of this project has been to evaluate the utility of digital spectral imagery at two levels of resolution for large scale, accurate, auto-classification of land cover along the Central California Coast. Although remote sensing technology offers obvious advantages over on-the-ground mapping, there are substantial trade-offs that must be made between resolving power and costs. Higher resolution images can theoretically be used to identify smaller habitat patches, but they usually require more scenes to cover a given area and processing these images is computationally intense requiring much more computer time and memory. Lower resolution images can cover much larger areas, are less costly to store, process, and manipulate, but due to their larger pixel size can lack the resolving power of the denser images. This lack of resolving power can be critical in regions such as the Central California Coast where important habitat change often occurs on a scale of 10 meters. Our approach has been to compare vegetation and habitat classification results from two aircraft-based spectral scenes covering the same study area but at different levels of resolution with a previously produced ground-truthed land cover base map of the area. Both of the spectral images used for this project were of significantly higher resolution than the satellite-based LandSat scenes used in the C-CAP program. The lower reaches of the Elkhorn Slough watershed was chosen as an ideal study site because it encompasses a suite of important vegetation types and habitat loss processes characteristic of the central coast region. Dramatic habitat alterations have and are occurring within the Elkhorn Slough drainage area, including erosion and sedimentation, land use conversion, wetland loss, and incremental loss due to development and encroachnnent by agriculture. Additonally, much attention has already been focused on the Elkhorn Slough due to its status as a National Marine Education and Research Reserve and as part of the Monterey Bay National Marine Sanctuary. These destinations have resulted in a rich collection of prior spatial and temporal habitat data.
An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps between the corresponding OBB and OBP models. For computational efficiency, the process is started at the coarsest resolution and stopped as soon as possible, preferably before reaching the finest resolution. At the coarsest resolution, there is a single OBB enclosing all relevant external objects and a single OBB enclosing the entire robot. At the next finer level of resolution, the coarsest-resolution OBB is divided into two OBBs, and so forth. If no collision is detected at the coarsest resolution, then there is no need for further computation to detect collisions. If a collision is detected at the coarsest resolution, then tests for collisions are performed at the next finer level of resolution. This process is continued to successively finer resolutions until either no more collisions are detected or the finest resolution is reached.
PISCES, the Pacific International Space Center for Exploration Systems. This paper describes the PISCES development plans, particularly in the areas of In-Situ Resource Utilization, Robotics and Education and Outreach.
In this paper we present MEXEC - a lightweight on-board planning and execution system that monitors spacecraft state to robustly respond to current conditions. In addition it projects the remaining plan forward in time to detect conflicts and revise the plan. Most current planetary missions use sequence based commanding from the ground,which limits the ability to respond to on-board state varying from planned for state. This results in planning for worst-case execution time, power utilization, data volume and other resources and leads to under utilization of the spacecraft capability. It also limits the ability to respond to faults. Due to the high radiation environment at Jupiter the probability of flight software resets is high. Therefore, of particular interest to the planned Europa Mission is the capability to restart the science plan after flight software resets. In this paper we present results from running Europa flyby scenarios with flight software resets in the Europa flight software test environment. Preliminary results with the prototype scenario show MEXEC takes less than a tenth of a second to respond to resets. The development was done as part of Europa-focused flight software, but MEXEC was designed to be applicable to landers and rovers as well.
The paper presents an overview of the ground rules, assumptions, methodology, operations model, element designs, base site plan, and quantitative findings. These findings include the performance of various regolith and ice resource utilization schemes as a function of base location and lunar surface parameters. The paper closes with short lists of the highest priority experiments and demonstrations needed on the lunar surface to retire key planning unknowns.
Dumas, Briggs, Reid and Smith (1989) describe the need for identifying mutually acceptable methodologies for developing standard agreements for the exchange of tracking time or facility use among international components. One possible starting point is the current process used at the Jet Propulsion Laboratory (JPL) in planning the use of tracking resources. While there is a significant promise of better resource utilization by international cooperative agreements, there is a serious challenge to provide convenient user participation given the separate project and network locations. Coordination among users and facility providers will require a more decentralized communication process and a wider variety of automated planning tools to help users find potential exchanges. This paper provides a framework in which international cooperation in the utilization of ground based space communication systems can be facilitated.
As part of the planned manned mission to Mars, NASA has noticed that shipping oxygen as a part of life support to keep the astronauts alive continuously is overly expensive, and impractical. As such, noting that the Martian atmosphere is 95.37% CO2, NASA chemists noted that one could obtain oxygen from the Martian atmosphere. The plan, as part of a larger ISRU (in-situ resource utilization) initiative, would extract water from the regolith, or the Martian soil which can be electrolyzed by solar panel produced voltage into hydrogen and oxygen. The hydrogen can then be used in the Sabatier reaction with carbon dioxide to produce methane and water producing a net reaction that does not lose water and outputs methane and oxygen for use as rocket fuel and breathing.
Pinyon-juniper woodlands (PJW) provide critical and resilient habitat for the local mammal and small bird species of Arizona's northern xeric environment. Drought in Arizona has been persistent for many decades, yet in 2021 PJW experienced a mass tree mortality event at the Wupatki National Monument (WNM) and in other areas across the American Southwest. Previously, researchers at the National Park Service (NPS) and the team from the NASA DEVELOP National Program attempted to quantify the extent of mortality in Northern Arizona between 2015 and 2021 using high resolution National Agricultural Imagery Program (NAIP) aerial photographs. This project aimed to improve the previous term’s methodology and expanded the comparison of the post-mortality event in 2021 to include tree cover assessments for 2017 and 2019. In this iteration, the team utilized NAIP imagery in conjunction with Landscape Fire and Resource Management Planning Tools (LANDFIRE) to calculate the total difference in PJW mortality using an unsupervised classification model trained from multi-date Modified Soil-Adjusted Vegetation Index (MSAVI) and the Visible Atmospherically Resistant Index (VARI) data for the study area. The research also assessed correlations between tree mortality and environmental factors using Western Land Data Assimilation System (WLDAS) modelled climate data. Average PJW mortality from 2015 to 2021 was 21.63% including 19.8% in WNM with the vast majority of dieback occurring between 2019 and 2021. The correlations were weak with the most correlated variables being bare soil evaporation (0.15), rainfall (0.14), groundwater storage (0.13), and wind speed (0.12), perhaps indicating drought as a likely driver of PJW mortality.