Active Constraints/Virtual Fixtures: A Survey

Stuart A Bowyer, Brian Davies, Ferdinando Rodriguez y Baena

IEEE Transactions on Robotics · 2013 · 305 citations · 93 references

Concepts

TL;DR

Active constraints, or virtual fixtures, are high‑level control algorithms that monitor a robotic manipulator relative to its environment and task, anisotropically regulating motion to guide users along task‑specific paths or confine them to safe regions. This paper surveys the diverse methods for applying active constraints in man‑machine collaborative manipulation. The survey organizes the literature around a three‑step framework—constraint definition, evaluation, and enforcement—and presents all relevant research approaches for each step.

Abstract

Active constraints, also known as virtual fixtures, are high-level control algorithms which can be used to assist a human in man-machine collaborative manipulation tasks. The active constraint controller monitors the robotic manipulator with respect to the environment and task, and anisotropically regulates the motion to provide assistance. The type of assistance offered by active constraints can vary, but they are typically used to either guide the user along a task-specific pathway or limit the user to within a “safe” region. There are several diverse methods described within the literature for applying active constraints, and these are surveyed within this paper. The active constraint research is described and compared using a simple generalized framework, which consists of three primary processes: 1) constraint definition, 2) constraint evaluation, and 3) constraint enforcement. All relevant research approaches for each of these processes, found using search terms associated to “virtual fixture,” “active constraint” and “motion constraint,” are presented.

References

93