NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Collections About News Help Login
Back to Results
Predictive Interfaces for Long-Distance Tele-OperationsWe address the development of predictive tele-operator interfaces for humanoid robots with respect to two basic challenges. Firstly, we address automating the transition from fully tele-operated systems towards degrees of autonomy. Secondly, we develop compensation for the time-delay that exists when sending telemetry data from a remote operation point to robots located at low earth orbit and beyond. Humanoid robots have a great advantage over other robotic platforms for use in space-based construction and maintenance because they can use the same tools as astronauts do. The major disadvantage is that they are difficult to control due to the large number of degrees of freedom, which makes it difficult to synthesize autonomous behaviors using conventional means. We are working with the NASA Johnson Space Center's Robonaut which is an anthropomorphic robot with fully articulated hands, arms, and neck. We have trained hidden Markov models that make use of the command data, sensory streams, and other relevant data sources to predict a tele-operator's intent. This allows us to achieve subgoal level commanding without the use of predefined command dictionaries, and to create sub-goal autonomy via sequence generation from generative models. Our method works as a means to incrementally transition from manual tele-operation to semi-autonomous, supervised operation. The multi-agent laboratory experiments conducted by Ambrose et. al. have shown that it is feasible to directly tele-operate multiple Robonauts with humans to perform complex tasks such as truss assembly. However, once a time-delay is introduced into the system, the rate of tele\ioperation slows down to mimic a bump and wait type of activity. We would like to maintain the same interface to the operator despite time-delays. To this end, we are developing an interface which will allow for us to predict the intentions of the operator while interacting with a 3D virtual representation of the expected state of the robot. The predictive interface anticipates the intention of the operator, and then uses this prediction to initiate appropriate sub-goal autonomy tasks.
Document ID
20060015673
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Wheeler, Kevin R. (NASA Ames Research Center Moffett Field, CA, United States)
Martin, Rodney (NASA Ames Research Center Moffett Field, CA, United States)
Allan, Mark B. (QSS Group, Inc. Moffett Field, CA, United States)
Sunspiral, Vytas (QSS Group, Inc. Moffett Field, CA, United States)
Date Acquired
August 23, 2013
Publication Date
September 5, 2005
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Meeting Information
Meeting: International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS 2005)
Location: Munich
Country: Germany
Start Date: September 5, 2005
End Date: September 8, 2005
Sponsors: European Space Agency, Japan Aerospace Exploration Agency, Canadian Space Agency, Centre National d'Etudes Spatiales, Deutsches Zentrum fuer Luft- und Raumfahrt (DLR), NASA Headquarters
Distribution Limits
Public
Copyright
Public Use Permitted.

Related Records

There are no records associated with this record.
No Preview Available