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This paper addresses structures, actions and technologies that contribute to real team development of a distributed team, and the leadership skills and tools that are used to implement that team development.
The purpose of this paper is to look for links in a virtual trainee's interest and self-efficacy in a simulated event as it relates to their previous self-reported technical skill level. Ultimately, the idea would be to provide the right amount of support at the right place at the right time to set the conditions for maximum transfer of the skill sets to the work place. An anecdotal recap of a recent experiment of a medium-scale training event produced in a virtual world will provide examples for discussion. In July 2010, a virtual training event was produced for the Air Force Research Lab's Games for Team Training (GaMeTT) at the Patriot Exercise at Volk Field in Wisconsin. There were 29 EMEDS participants who completed the simulated OCO event using the OLIVE gaming engine. Approximately 25 avatars were present at any given time; including role players, observers, coordinators and participants.
Distributed search algorithms are crucial in dealing with large optimization problems, particularly when a centralized approach is not only impractical but infeasible. Many machine learning concepts have been applied to search algorithms in order to improve their effectiveness. In this article we present an algorithm that blends Reinforcement Learning (RL) and hill climbing directly, by using the RL signal to guide the exploration step of a hill climbing algorithm. We apply this algorithm to the domain of a constellations of communication satellites where the goal is to minimize the loss of importance weighted data. We introduce the concept of 'ghost' traffic, where correctly setting this traffic induces the satellites to act to optimize the world utility. Our results indicated that the bi-utility search introduced in this paper outperforms both traditional hill climbing algorithms and distributed RL approaches such as team games.
This paper describes a measurement methodology developed for assessing the readiness, and identifying opportunities for improving the effectiveness, of distributed collaborative design teams preparing to conduct a coccurent design session.
The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.
Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.
Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.
Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.
Established at the NASA Glenn Research Center (GRC) in 2006 to meet the need for rapid mission analysis and multi-disciplinary systems design for in-space and human missions, the Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team is a multidisciplinary, concurrent engineering group whose primary purpose is to perform integrated systems analysis, but it is also capable of designing any system that involves one or more of the disciplines present in the team. The authors were involved in the development of the COMPASS team and its design process, and are continuously making refinements and enhancements. The team was unofficially started in the early 2000s as part of the distributed team known as Team JIMO (Jupiter Icy Moons Orbiter) in support of the multi-center collaborative JIMO spacecraft design during Project Prometheus. This paper documents the origins of a concurrent mission and systems design team at GRC and how it evolved into the COMPASS team, including defining the process, gathering the team and tools, building the facility, and performing studies.
The NOW (Nanosatellite Orbital Workshop) of NASA Ames Research Center (ARC) has two cubesats in orbit at this time: 6 U TechEdSat-10 (T-10) and the 3U TechEdSat-7 (T-7). T10 was jettisoned from the ISS via the NANORACKS system 7/13/2020, and T-7 was launched via Virgin Orbit 1/17/2021. Both were built by the Nano-satellite Orbital Workshop (NOW) at NASA ARC, and designed and fabricated by interns and students in collaboration with educational institutions. Prototyping novel technologies for non-powered re-entry and communications from orbit are primary research interests, however all subsystems including power generation and distribution, subsystem control, navigation, positioning, heat management etc. extend current technologies. Use of distributed processors using open software platforms and standards other based technologies and software is integral to all segments of spacecraft design. Here, we will present an overview of the spacecraft, experiments, and accomplishments – as well as the next three flight experiments. Some of these experiments include: The exo-brake re-entry system is being developed to enable sample return and end of life disposal; Internal communications for sensors, inter-subsystem and experiments uses both a Zigbee based PAN and internal Wi-Fi for high-speed inter-device communications; The Iridium small message LEO system (Short Burst Data) is used to both command the spacecraft and send data to the ground; Experimental use of the Global-Star system for L-band system comparison and back-up; Collaborative NOAA an experiment to communicate from LEO to the GOES geostationary satellite using the DCS (Data Collection System) with on-board Doppler correction; Mars and Lunar experimental communication systems for future cis-lunar and interplanetary nano-satellites; First demonstration of the NASA Near Earth Network systems with nano-satellites at NASA/Wallops Island; Solar array design and implementation for unique future flexible structures; Power distribution using Tardigrade rad-hard processor omni-board (designed by the team); Distributed processors with internal Wi-Fi connectivity; and Initial experiments with AI/Machine Learning.
Success of exploration missions will depend on skilled performance by a distributed team that includes both the astronauts in space and Mission Control personnel. Coordinated and collaborative teamwork will be required to cope with challenging complex problems in a hostile environment. While thorough preflight training and procedures will equip creW'S to address technical problems that can be anticipated, preparing them to solve novel problems is much more challenging. This presentation will review components of effective team performance, challenges to effective teamwork, and strategies for ensuring effective team performance. Teamwork skills essential for successful team performance include the behaviors involved in developing shared mental models, team situation awareness, collaborative decision making, adaptive coordination behaviors, effective team communication, and team cohesion. Challenges to teamwork include both chronic and acute stressors. Chronic stressors are associated with the isolated and confined environment and include monotony, noise, temperatures, weightlessness, poor sleep and circadian disruptions. Acute stressors include high workload, time pressure, imminent danger, and specific task-related stressors. Of particular concern are social and organizational stressors that can disrupt individual resilience and effective mission performance. Effective team performance can be developed by training teamwork skills, techniques for coping with team conflict, intracrew and intercrew communication, and working in a multicultural team; leadership and teamwork skills can be fostered through outdoor survival training exercises. The presentation will conclude with an evaluation of the special requirements associated with preparing crews to function autonomously in long-duration missions.
In this paper we discuss how team configuration may influence how infor-mation is shared among team members for low-altitude Unmanned Aircraft Systems (UAS) operations. NASA collected and analyzed observation data gathered during a series of field tests for the UAS Traffic Management (UTM) project. The field tests were part of a larger effort aimed at advancing the UTM concept, conducted at six test-sites spread across the USA. Ground control station (GCS) concepts, flight-crew composition, and crew-size var-ied within and across test-sites. Flight crews took two strategic approaches to organizing their teams. The first of the two approaches was implemented by one third of the flight crews. These crews integrated the role of UTM opera-tor into the duties of existing crew members, merging the current roles with this new one, keeping the UTM Operator collocated with the flight crew. The remaining two thirds implemented a distributed team configuration, where a single UTM operator distributed support across multiple crews. Results from our data collection efforts revealed that UTM Operator location influenced whether flight crews used verbal communication versus displays to acquire UTM information.
Returning samples from Mars has long been a major planetary science objective due to the high scientific value and transformative potential of the resulting data. An exciting dimension of this objective is the potential for the detection of ancient microbiological life, and the possibility of improving our understanding of the evolution of habitable environments on Mars and the development of life on Earth. To ensure that returned samples meet stringent planetary protection requirements and do not expose Earth to potential biohazards, the joint NASA/ESA Sample Receiving Project (SRP) assembled the Sample Safety Assessment Protocol Tiger Team (SSAP-TT). Members were recruited with the specific goal of creating a multi-disciplinary and internationally distributed team of experts in their respective fields across the federal government, academia, and private industry. This team was chartered with reassessing previous sample safety assessment strategies, defining what constitutes a biological hazard, developing a protocol to test for potential biohazards, and establishing a statistical framework to determine if samples are “safe” for release. The team developed a three-step protocol, supported by a Bayesian statistical framework, to assess whether returned samples contain potential biohazards that could present a risk to Earth’s biosphere. Initial conclusions indicated that an effective and comprehensive safety assessment protocol is feasible using modern techniques and does not require an excessive amount of sample consumption or traditional microbiological detection methodology. Herein, we will present an overview of the MSR SRP, the proposed safety assessment protocol, and how aspects of this novel approach can be applied to biological assessment in healthcare product manufacturing practices.
The Habitat Demonstration Unit (HDU) project team constructed an analog prototype lunar surface laboratory called the Pressurized Excursion Module (PEM). The prototype unit subsystems were integrated in a short amount of time, utilizing a rapid prototyping approach that brought together over 20 habitation-related technologies from a variety of NASA centers. This paper describes the system integration strategies and lessons learned, that allowed the PEM to be brought from paper design to working field prototype using a multi-center team. The system integration process was based on a rapid prototyping approach. Tailored design review and test and integration processes facilitated that approach. The use of collaboration tools including electronic tools as well as documentation enabled a geographically distributed team take a paper concept to an operational prototype in approximately one year. One of the major tools used in the integration strategy was a coordinated effort to accurately model all the subsystems using computer aided design (CAD), so conflicts were identified before physical components came together. A deliberate effort was made following the deployment of the HDU PEM for field operations to collect lessons learned to facilitate process improvement and inform the design of future flight or analog versions of habitat systems. Significant items within those lessons learned were limitations with the CAD integration approach and the impact of shell design on flexibility of placing systems within the HDU shell.
In March 2007, NASA issued revised rules for space flight project management, NPR 7120.5D, 'NASA Space Flight Program and Project Management Requirements.' Central to the new rules was the construct of Key Decision Points, maturity gates that the project team must pass in order to continue development. In order that the KDP decision be fully informed, the NPR required, as entrance criteria for the gate, the generation and delivery of specified planning, technical, and cost/schedule documents (gate products) and a life-cycle review, the Preliminary Design Review. Building on JPL experience on the Prometheus and Juno projects, the team successfully organized for and conducted these reviews on an aggressive schedule. Key actions were taken to proactively interact with the SRB, produce high-quality gate products with stakeholder review, generate review presentation materials, and handle a myriad of supporting logistical functions. A review preparation team was established, including a Review Captain and leads for documentation, information systems, and logistics, and their roles, responsibilities and task assignments were identified. Aids were produced, including a detailed review preparation schedule and a comprehensive gate products production table. Institutional support was leveraged early and often. Implementation strategy reflected the needs of a nationally-distributed team, as well as applicable export control and IT security requirements. This paper gives a brief overview of the GRAIL mission and its project management challenges, provides a detailed description of project PMSR and PDR preparation and execution activities, including positive and negative lessons learned, and identifies recommendations for future NASA (and non-NASA) project teams.
SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.
Total quality management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The Assured Crew Return Vehicle (ACRV) Project Office was identified as an excellent project in which to demonstrate the applications and benefits of TQM processes. As the ACRV Program moves through its various stages of development, it is vital that effectiveness and efficiency be maintained in order to provide the Space Station Freedom (SSF) crew an affordable, on-time assured return to Earth. A critical factor for the success of the ACRV is attaining the maximum benefit from the resources applied to the program. Through a series of four tutorials on various quality improvement techniques, and numerous one-on-one sessions during the SSF's 10-week term in the project office, results were obtained which are aiding the ACRV Office in implementing a disciplined, ongoing process for generating fundamental decisions and actions that shape and guide the organization. Significant advances were made in improving the processes for two particular groups - the correspondence distribution team and the WATER Test team. Numerous people from across JSC were a part of the various team activities including engineering, man systems, and safety. The work also included significant interaction with the support contractor to the ACRV Project. The results of the improvement activities can be used as models for other organizations desiring to operate under a system of continuous improvement. In particular, they have advanced the ACRV Project Teams further down the path of continuous improvement, in support of a working philosophy of TQM.
Now that the International Space Station is undergoing assembly, NASA is strategizing about the next logical exploration strategy for robotic missions and the next destination for humans. NASA's current efforts are in developing technologies that will both aid the robotic exploration strategy and make human flight to other celestial bodies both safe and affordable. One of these enabling technologies for future robotic and human exploration missions is aeroassist. This paper will (1) define aeroassist, (2) explain the benefits and uses of aeroassist, and (3) describe a method, currently used by the NASA Aeroassist Working Group, by which widely geographically distributed teams can assemble, present, use, and archive technology information.