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Teleoperation and Visualization Interfaces for Remote Intervention in Space Approaches to robotic manufacturing, assembly, and servicing of in-space assets range from autonomous operation to direct teleoperation, with many forms of semi-autonomous teleoperation in between. Because most approaches require one or more human operators at some level, it is important to explore the control and visualization interfaces available to those operators, taking into account the challenges due to significant telemetry time delay. We consider one motivating application of remote teleoperation, which is ground-based control of a robot on-orbit for satellite servicing. This paper presents a model-based architecture that: 1) improves visualization and situation awareness, 2) enables more effective human/robot interaction and control, and 3) detects task failures based on anomalous sensor feedback. We illustrate elements of the architecture by drawing on 10 years of our research in this area. The paper further reports the results of several multi-user experiments to evaluate the model-based architecture, on ground-based test platforms, for satellite servicing tasks subject to round-trip communication latencies of several seconds. The most significant performance gains were obtained by enhancing the operators’ situation awareness via improved visualization and by enabling them to precisely specify intended motion. In contrast, changes to the control interface, including model-mediated control or an immersive 3D environment, often reduced the reported task load but did not significantly improve task performance. Considering the challenges of fully autonomous intervention, we expect that some form of teleoperation will continue to be necessary for robotic in-situ servicing, assembly, and manufacturing tasks for the foreseeable future. We propose that effective teleoperation can be enabled by modeling the remote environment, providing operators with a fused view of the real environment and virtual model, and incorporating interfaces and control strategies that enable interactive planning, precise operation, and prompt detection of errors.
Document ID
20210018087
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Peter Kazanzides
(Johns Hopkins University Baltimore, Maryland, United States)
Balazs P. Vagvolgyi
(Johns Hopkins University Baltimore, Maryland, United States)
Will Pryor
(Johns Hopkins University Baltimore, Maryland, United States)
Anton Deguet
(Johns Hopkins University Baltimore, Maryland, United States)
Simon Leonard
(Johns Hopkins University Baltimore, Maryland, United States)
Louis L. Whitcomb
(Johns Hopkins University Baltimore, Maryland, United States)
Date Acquired
June 30, 2021
Publication Date
December 1, 2021
Publication Information
Publication: Frontiers in Robotics and AI
Publisher: Frontiers Media
Volume: 8
Issue Publication Date: December 1, 2021
e-ISSN: 2296-9144
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Funding Number(s)
WBS: 000278
CONTRACT_GRANT: NNG15CR66C
CONTRACT_GRANT: NNG10CR16C
CONTRACT_GRANT: NNG14CR58C
CONTRACT_GRANT: NSF IIS-1208540
CONTRACT_GRANT: NSF EEC-1460674
CONTRACT_GRANT: NSF NRI-1637789
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Peer Committee
Keywords
space robotics
teleoperation
scene modeling
model-mediated control
satellite servicing
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