Abstract
We describe our current progress in developing Human-Machine Collaborative Systems (HMCSs) for microsurgical applications such as vitreo-retinal eye surgery. Three specific problems considered here are (1) developing of systems tools for describing and implementing an HMCS, (2) segmentation of complex tasks into logical components given sensor traces of a human performing the task, and (3) measuring HMCS performance. Our goal is to integrate these into a full microsurgical workstation with the ability to automatically “parse” traces of user execution into a task model which is then loaded into the execution environment, providing the user with assistance using online recognition of task state. The major contributions of our work to date include an XML task graph modeling framework and execution engine, an algorithm for real-time segmentation of user actions using continuous Hidden Markov Models, and validation techniques for analyzing the performance of HMCSs.
An Erratum for this chapter can be found at http://dx.doi.org/10.1007/978-3-540-31508-7_64
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© 2005 Springer-Verlag Berlin Heidelberg
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Kragic, D., Marayong, P., Li, M., Okamura, A.M., Hager, G.D. (2005). Retracted: Human-Machine Collaborative Systems for Microsurgical Applications. In: Dario, P., Chatila, R. (eds) Robotics Research. The Eleventh International Symposium. Springer Tracts in Advanced Robotics, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11008941_18
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DOI: https://doi.org/10.1007/11008941_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23214-8
Online ISBN: 978-3-540-31508-7
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