A micro- and macro- analysis of human-machine interfaces and systems in space
Author(s)Joseph, Christine,S.M.Massachusetts Institute of Technology.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Institute for Data, Systems, and Society.
Technology and Policy Program.
Leia Stirling and Danielle Wood.
MetadataShow full item record
Humans and machines interact with each other on a variety of scales. Interactions can involve tightly coupled interfaces or even be socio-technical in nature. In terms of large complex systems, humans learn to interact and access these systems in the context of dierent social, political, technical, and economic environments. And yet despite this breadth, research on human-machine interactions on all scales depends on having metrics for evaluation and platforms upon which measurement can take place. This thesis investigated the utilization of new metrics for studying human-machine interfaces and systems at a micro and macro scale. At the micro scale, we investigated how humans may strategize to move their bodies in order to complete a agility-based running tasks. For a slalom course, an optimal control model was formulated to analyze the characteristics of an optimal path trajectory to complete the task as quickly as possible.Opportunities to improve the model were informed by the utilization of a \micro" system - wearable inertial measurement unit (IMU) devices. While the path trajectories estimated from these devices have limitations, IMUs offer an opportunities to measure human movement in natural operational environments. In the context of space exploration, such natural environments could also include planetary surfaces with reduced gravity. To evaluate how locomotion might change in such conditions, the optimal control model was used to investigate how an optimal path trajectory would change while completing the slalom task in reduced gravity. The results demonstrated that as gravity decreased, it would take a human more time to complete the task and the curvature about turning regions would decrease (wider turns).The results and limitations of the model in nominal and reduced gravity conditions demonstrated the strong influences gravity and ground reaction forces have on the path trajectories humans can execute. Investigating some of the limitations of the optimal models depended on having experimental trajectories estimated from the IMUs as a platform of measurement. Reflecting on how the curvature of the path trajectories decreased as gravity decreased, the metric of integrated curvature was proposed for analyzing the path trajectories of humans completing an agility task. The feasibility of using this metric was analyzed via a pilot study of another agility-based running task. Along with other common metrics of characterizing agility and path trajectories (task completion time and path length), the integrated curvature metric was evaluated using both optical motion capture (Vicon) and wearable IMU measurement platforms.The pilot study results demonstrated that subject performance in terms of completion time, path length, and integrated curvature could depend on the structure of the task and whether a subject had a priori knowledge of the task goal. Furthermore, the results demonstrate that there are opportunities to leverage the integrated curvature metric via the wearable IMU measurement platform to make decision-making conclusions. Wearable IMUs offer a measurement platform that could be utilized in natural field settings, including reduced gravity planetary environments. But in order to test out and improve metrics for IMUs in these conditions, we require access to reduced gravity research platforms. Accessibility to microgravity platforms is complex and dependent on a variety of factors beyond just financial costs.And just as it is important to use human performance measurement platforms and metrics that can be leveraged in dierent operational environments for generalized user populations, it also important that access to microgravity research platforms is available for non-traditional partners. Non-traditional partners include users like startups, early career academics, emerging space nations, and education outreach groups. In order to capture the complexities and nuances behind accessibility for end users in the microgravity research ecosystem, new metrics of economic openness and administrative openness were proposed. The current and future microgravity research ecosystems were surveyed using case study research methods. Systems architecture methods were utilized to analyze the stakeholders and forms of access (pathways) present in the ecosystem.Analysis demonstrated that mixed public/private pathways can foster relatively high economic and administrative openness, but these levels of openness can decrease dependent on the capabilities and type of the end user and the type of funding sources used at dierent stages of the pathway. Opportunities exist to refine the accessibility metrics and add new dimensions of analysis. Whether it be for wearable devices or microgravity research, by refining metrics and examining platforms now, we can help ensure accessibility to these systems for any type of user in the future.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 153-165).
DepartmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Institute for Data, Systems, and Society; Technology and Policy Program
Massachusetts Institute of Technology
Aeronautics and Astronautics., Institute for Data, Systems, and Society., Technology and Policy Program.