Vision-assisted control for manipulation using virtual fixtures

Alessandro Bettini, Panadda Marayong, Samuel Lang, Allison M. Okamura, Gregory D. Hager

Research output: Contribution to journalArticlepeer-review

190 Scopus citations


We present the design and implementation of a vision-based system for cooperative manipulation at millimeter to micrometer scales. The system is based on an admittance control algorithm that implements a broad class of guidance modes called virtual fixtures. A virtual fixture, like a real fixture, limits the motion of a tool to a prescribed class or range of motions. We describe how both hard (unyielding) and soft (yielding) virtual fixtures can be implemented in this control framework. We then detail the construction of virtual fixtures for point positioning and curve following as well as extensions of these to tubes, cones, and sequences thereof. We also describe an implemented system using the JHU Steady Hand Robot. The system uses computer vision as a sensor for providing a reference trajectory, and the virtual fixture control algorithm then provides haptic feedback to implemented direct, shared manipulation. We provide extensive experimental results detailing both system performance and the effects of virtual fixtures on human speed and accuracy.

Original languageEnglish (US)
Pages (from-to)953-966
Number of pages14
JournalIEEE Transactions on Robotics
Issue number6
StatePublished - Dec 2004


  • Human-machine systems
  • Robot control
  • Virtual fixtures
  • Visual servoing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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