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The intelligent copilot: A constraint-based approach to shared-adaptive control of ground vehicles
Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge, MA, USA.
Quantum Signal, LLC, Saline, MI, USA.
2013 (English)In: IEEE Intelligent Transportation Systems Magazine, ISSN 1939-1390, Vol. 5, no 2, 45-54 p.Article in journal (Refereed) Published
Abstract [en]

This work presents a new approach to semi-autonomous vehicle hazard avoidance and stability control, based on the design and selective enforcement of constraints. This differs from traditional approaches that rely on the planning and tracking of paths and facilitates minimally-invasive control for human-machine systems. Instead of forcing a human operator to follow an automation-determined path, the constraint-based approach identifies safe homotopies, and allows the operator to navigate freely within them, introducing control action only as necessary to ensure that the vehicle does not violate safety constraints. This method evaluates candidate homotopies based on restrictiveness rather than traditional measures of path goodness, and designs and enforces requisite constraints on the human's control commands to ensure that the vehicle never leaves the controllable subset of a desired homotopy. This paper demonstrates the approach in simulation and characterizes its effect on human teleoperation of unmanned ground vehicles via a 20-user, 600-trial study on an outdoor obstacle course. Aggregated across all drivers and experiments, the constraintbased control system required an average of 43% of the available control authority to reduce collision frequency by 78% relative to traditional teleoperation, increase average speed by 26%, and moderate operator steering commands by 34%. © 2009-2012 IEEE

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2013. Vol. 5, no 2, 45-54 p.
National Category
Robotics
Identifiers
URN: urn:nbn:se:hh:diva-20610DOI: 10.1109/MITS.2013.2247796ISI: 000209299100008Scopus ID: 2-s2.0-84877736298OAI: oai:DiVA.org:hh-20610DiVA: diva2:585328
Note

This material is based on work supported by the US ARO under contract W911NF-11-1-0046 and DARPA DSO under the M3 program.

Available from: 2013-01-09 Created: 2013-01-09 Last updated: 2015-09-29Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
  • en-GB
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Output format
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