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Marquez, Jessica J.

Publications and source records attributed to Marquez, Jessica J..

At least 19 records

Designing for Astronaut-Centric Planning and Scheduling Aids

We have investigated and evaluated a novel concept of operations for human spaceflight: allowing astronauts to manage and schedule their own timeline. In order to evaluate this self-scheduling concept of operations, we have designed, implemented, and field-tested astronaut-centric planning and scheduling aid. Our mobile-based software aid, Playbook, has been used in a variety of Earth analogs as well as onboard the International Space Station. We will demonstrate the unique Playbook features that we have developed based on research findings during field testing that facilitate planning and scheduling in extreme environments.

planning and scheduling

Lessons Learned from International Space Station Crew Autonomous Scheduling Test

In 2017, our team investigated and evaluated the novel concept of operations of astronaut self-scheduling (rescheduling their own timeline without creating violations) onboard International Space Station (ISS). Five test sessions were completed for this technology demonstration called Crew Autonomous Scheduling Test (CAST). For the first time in a spaceflight operational environment, an ISS crewmember planned, rescheduled, and executed their activities in real-time on a mobile device while abiding by flight and scheduling constraints. This paper discusses the lessons learned from deployment to execution.

planning and scheduling

Human-Automation Allocations for Current Robotic Space Operations: Space Station Remote Manipulator System

NASA’s Human Research Program’s Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) delineates the uncertainty surrounding crew work with automation and robotics in spaceflight. HARI is concerned with detrimental effects of ineffective user interfaces, system designs and/or functional task allocation on crew performance, potentially compromising mission success and safety. This risk arises because of limited experience with complex automation and robotics in spaceflight. One key knowledge gap within the HARI risk is related to function allocation.

Chang, Mai Lee

Human-Automation Allocations for Current Robotic Space Operations

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.

robotic allocation

Playbook Data Analysis Tool: Collecting Interaction Data from Extremely Remote Users

Typically, user tests for software tools are conducted in person. At NASA, the users may be located at the bottom of the ocean in a pressurized habitat, above the atmosphere in the International Space Station, or in an isolated capsule on a simulated asteroid mission. The Playbook Data Analysis Tool (P-DAT) is a human-computer interaction (HCI) evaluation tool that the NASA Ames HCI Group has developed to record user interactions with Playbook, the group's existing planning-and-execution software application. Once the remotely collected user interaction data makes its way back to Earth, researchers can use P-DAT for in-depth analysis. Since a critical component of the Playbook project is to understand how to develop more intuitive software tools for astronauts to plan in space, P-DAT helps guide us in the development of additional easy-to-use features for Playbook, informing the design of future crew autonomy tools.P-DAT has demonstrated the capability of discreetly capturing usability data in amanner that is transparent to Playbook’s end-users. In our experience, P-DAT data hasalready shown its utility, revealing potential usability patterns, helping diagnose softwarebugs, and identifying metrics and events that are pertinent to Playbook usage aswell as spaceflight operations. As we continue to develop this analysis tool, P-DATmay yet provide a method for long-duration, unobtrusive human performance collectionand evaluation for mission controllers back on Earth and researchers investigatingthe effects and mitigations related to future human spaceflight performance.

in-flight monitoring

Increasing Crew Autonomy for Long Duration Exploration Missions: Self-Scheduling

Over the last three years, we have been investigating the operational concept of crew self-scheduling as a method of increasing crew autonomy for future exploration missions. Through Playbook, a planning and scheduling software tool, we have incrementally increased the ability for Earth analog mission crews to modify their schedules. Playbook allows the crew to add new activities from scratch, add new activities or groups of activities through a Task List, and reschedule or reassign flexible activities. The crew is also able to identify if plan modifications create violations, i.e., plan constraints not being met. This paper summarizes our observations with qualitative evidence from four NASA Extreme Environment Mission Operations (NEEMO) analog missions that supported self-scheduling as a feasible operational concept.

planning and scheduling

Future Exploration Missions' Tasks Associated with the Risk of Inadequate Design of Human and Automation/Robotic Integration

NASA's Human Research Program (HRP) funds research efforts aimed at mitigating various human health and performance risks, including the Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI). As such, within HRP, the Human Factors and Behavioral Performance (HFBP) Element tasked an evaluation of future HARI needs in order to scope and focus the HARI risk research plan. The objective was to provide a systematic understanding of the critical factors associated with effective HARI that will be necessary to achieve the future mission goals for near- and deep-space exploration. Future mission goals are specified by NASA Design Reference Missions (DRMs) that are pertinent to the HRP. The outcome of this evaluation is a set of NASA-relevant HARI tasks, factors, and interactions required for exploration-class missions.

space operations

Minerva: User-Centered Science Operations Software Capability for Future Human Exploration

In June of 2016, the Biologic Analog Science Associated with Lava Terrains (BASALT) research project conducted its first field deployment, which we call BASALT-1. BASALT-1 consisted of a science-driven field campaign in a volcanic field in Idaho as a simulated human mission to Mars. Scientists and mission operators were provided a suite of ground software tools that we refer to collectively as Minerva to carry out their work. Minerva provides capabilities for traverse planning and route optimization, timeline generation and display, procedure management, execution monitoring, data archiving, visualization, and search. This paper describes the Minerva architecture, constituent components, use cases, and some preliminary findings from the BASALT-1 campaign.

Deans, Matthew

Increasing Crew Autonomy for Long Duration Exploration Missions: Self-Scheduling

Over the last three years, we have been investigating the operational concept of crew self-scheduling as a method of increasing crew autonomy for future exploration missions. Through Playbook, a planning and scheduling software tool, we have incrementally increased the ability for Earth analog mission crews to modify their schedules. Playbook allows the crew to add new activities from scratch, add new activities or groups of activities through a Task List, and reschedule or reassign flexible activities. The crew is also able to identify if plan modifications create violations, i.e., plan constraints not being met. This paper summarizes our observations with qualitative evidence from four NASA Extreme Environment Mission Operations (NEEMO) analog missions that supported self-scheduling as a feasible operational concept.

crew autonomy

Operational Assessment of Apollo Lunar Surface Extravehicular Activity

Quantifying the operational variability of extravehicular activity (EVA) execution is critical to help design and build future support systems to enable astronauts to monitor and manage operations in deep-space, where ground support operators will no longer be able to react instantly and manage execution deviations due to the significant communication latency. This study quantifies the operational variability exhibited during Apollo 14-17 lunar surface EVA operations to better understand the challenges and natural tendencies of timeline execution and life support system performance involved in surface operations. Each EVA (11 in total) is individually summarized as well as aggregated to provide descriptive trends exhibited throughout the Apollo missions. This work extends previous EVA task analyses by calculating deviations between planned and as-performed timelines as well as examining metabolic rate and consumables usage throughout the execution of each EVA. The intent of this work is to convey the natural variability of EVA operations and to provide operational context for coping with the variability inherent to EVA execution as a means to support future concepts of operations.

planning and scheduling

Becoming Earth Independent: Human-Automation-Robotics Integration Challenges for Future Space Exploration

Future exploration missions will require NASA to integrate more automation and robotics in order to accomplish mission objectives. This presentation will describe on the future challenges facing the human operator (astronaut, ground controllers) as we increase the amount of automation and robotics in spaceflight operations. It will describe how future exploration missions will have to adapt and evolve in order to deal with more complex missions and communication latencies. This presentation will outline future human-automation-robotic integration challenges.

human-robotic

Mission Planning for Robotic and Human Exploration

Mission planning for spaceflight is a complex challenge for ground operators managing robotic or human missions. It requires integrating the needs of various disciplines and creating an effective, efficient, and safe plan to execute. NASA uses specialized tools to meet planning requirements and constraints. This talk will provide an overview of spaceflight mission planning as well as the software tools the Human-Computer Interaction Group has built to support scheduling and planning. Also, it identifies the future scheduling and planning challenges for human Mars missions and how we leverage Earth Analogs to learn about Mars operations.

Scheduling and planning

Evaluation of Human and AutomationRobotics Integration Needs for Future Human Exploration Missions

NASA employs Design Reference Missions (DRMs) to define potential architectures for future human exploration missions to deep space, the Moon, and Mars. While DRMs to these destinations share some components, each mission has different needs. This paper focuses on the human and automation/robotic integration needs for these future missions, evaluating them with respect to NASA research gaps in the area of space human factors engineering. The outcomes of our assessment is a human and automation/robotic (HAR) task list for each of the four DRMs that we reviewed (i.e., Deep Space Sortie, Lunar Visit/Habitation, Deep Space Habitation, and Planetary), a list of common critical HAR factors that drive HAR design.

design reference missions

Integrating Human Performance Measures into Space Operations: Beyond Our Scheduling Capabilities?

Current planning and scheduling software tools for International Space Station (ISS) support different flight controller teams as they plan daily space operations. Planning and scheduling tools capabilities include integrating digitized ISS state inputs, evaluating their expected future states, and propagating them over time. Extensive, custom-made computational models of operations, of objectives, and of operational constraints help ISS flight controllers identify where scheduled events violate constraints. Based on the current capabilities of these tools, this paper proposes how human performance measures could be better integrated into planning and scheduling tools for space mission operations. Future integration of human performance measures could be applied to state inputs (in this case, the astronaut’s state) and to modeling human performance operational constraints & operational objectives (i.e., assigned activities) with parameters that are relevant to human performance measures. Gaps between the state-of-the-art for human performance modeling and planning tools for future exploration missions are identified.

space operations

Survey and Assessment of Crew Performance Evaluation Methods Applicable to Human Spacecraft Design

Space is an unforgiving environment where the actions of the crew play a critical role in their health and safety. Given the limited number of crewmembers typically onboard a spacecraft and the multitude of complex systems they must operate, the performance of each individual is of paramount importance. Spacecraft habitat layout and operations are two main drivers affecting crew performance efficiency. Having the capability to analyze and compare crew performance across various spacecraft configurations can help identify improvements early in the conceptual design process where changes are less costly to implement, ultimately reducing overall project costs and improving long-term operations of the system. Currently, there are few comprehensive methods readily available for evaluating crew integration within a spacecraft in the conceptual design phase. In order to address this shortcoming, the goal of this work was to analyze various specialized evaluation methods found in analogous industries that have potential application to human spacecraft design. A survey of more than 400 human performance evaluation methods was completed. Over twenty different attributes were identified for each method and a variety of analyses were conducted to characterize and evaluate their potential use for assessing human spacecraft design options. The analysis revealed a particular deficiency of quantitative evaluation methods that are applicable early in the systems engineering design phase. It also identified five existing methods that could be supplemented to achieve the needs of an early design evaluation method. Additional discussion describes potential issues that must be overcome when developing a method specific for use in human spacecraft evaluations.

crew performance

Level of Automation and Failure Frequency Effects on Simulated Lunar Lander Performance

A human-in-the-loop experiment was conducted at the NASA Ames Research Center Vertical Motion Simulator, where instrument-rated pilots completed a simulated terminal descent phase of a lunar landing. Ten pilots participated in a 2 x 2 mixed design experiment, with level of automation as the within-subjects factor and failure frequency as the between subjects factor. The two evaluated levels of automation were high (fully automated landing) and low (manual controlled landing). During test trials, participants were exposed to either a high number of failures (75% failure frequency) or low number of failures (25% failure frequency). In order to investigate the pilots' sensitivity to changes in levels of automation and failure frequency, the dependent measure selected for this experiment was accuracy of failure diagnosis, from which D Prime and Decision Criterion were derived. For each of the dependent measures, no significant difference was found for level of automation and no significant interaction was detected between level of automation and failure frequency. A significant effect was identified for failure frequency suggesting failure frequency has a significant effect on pilots' sensitivity to failure detection and diagnosis. Participants were more likely to correctly identify and diagnose failures if they experienced the higher levels of failures, regardless of level of automation

performance

Supporting Real-Time Operations and Execution through Timeline and Scheduling Aids

Since 2003, the NASA Ames Research Center has been actively involved in researching and advancing the state-of-the-art of planning and scheduling tools for NASA mission operations. Our planning toolkit SPIFe (Scheduling and Planning Interface for Exploration) has supported a variety of missions and field tests, scheduling activities for Mars rovers as well as crew on-board International Space Station and NASA earth analogs. The scheduled plan is the integration of all the activities for the day/s. In turn, the agents (rovers, landers, spaceships, crew) execute from this schedule while the mission support team members (e.g., flight controllers) follow the schedule during execution. Over the last couple of years, our team has begun to research and validate methods that will better support users during realtime operations and execution of scheduled activities. Our team utilizes human-computer interaction principles to research user needs, identify workflow processes, prototype software aids, and user test these. This paper discusses three specific prototypes developed and user tested to support real-time operations: Score Mobile, Playbook, and Mobile Assistant for Task Execution (MATE).

scheduling