title: Handheld Micromanipulation with Vision-Based Virtual Fixtures.
abstract: Precise movement during micromanipulation becomes difficult in submillimeter workspaces, largely due to the destabilizing influence of tremor. Robotic aid combined with filtering techniques that suppress tremor frequency bands increases performance; however, if knowledge of the operator's goals is available, virtual fixtures have been shown to greatly improve micromanipulator precision. In this paper, we derive a control law for position-based virtual fixtures within the framework of an active handheld micromanipulator, where the fixtures are generated in real-time from microscope video. Additionally, we develop motion scaling behavior centered on virtual fixtures as a simple and direct extension to our formulation. We demonstrate that hard and soft (motion-scaled) virtual fixtures outperform state-of-the-art tremor cancellation performance on a set of artificial but medically relevant tasks: holding, move-and-hold, curve tracing, and volume restriction.
authors.affiliation: Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213 USA ( camr@ri.cmu.edu ).
authors.forename: Brian C
authors.initials: BC
authors.lastname: Becker
authors.forename: Robert A
authors.initials: RA
authors.lastname: Maclachlan
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Hager
authors.forename: Cameron N
authors.initials: CN
authors.lastname: Riviere