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Visual Servoing

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Springer Handbook of Robotics

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Abstract

This chapter introduces visual servo control, using computer vision data in the servo loop to control the motion of a robot. We first describe the basic techniques that are by now well established in the field. We give a general overview of the formulation of the visual servo control problem, and describe the two archetypal visual servo control schemes: image-based and pose-based visual servo control. We then discuss performance and stability issues that pertain to these two schemes, motivating advanced techniques. Of the many advanced techniques that have been developed, we discuss two-and-a-half-dimensional (GlossaryTerm

2.5-D

), hybrid, partitioned, and switched approaches. Having covered a variety of control schemes, we deal with target tracking and controlling motion directly in the joint space and extensions to under-actuated ground and aerial robots. We conclude by describing applications of visual servoing in robotics.

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Abbreviations

2-D:

two-dimensional

2.5-D:

two-and-a-half-dimensional

3-D:

three-dimensional

IBVS:

image-based visual servo control

IMU:

inertial measurement unit

LQG:

linear quadratic Gaussian

MEMS:

microelectromechanical system

PBVS:

pose-based visual servo control

VS:

visual servo

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Author information

Authors and Affiliations

  1. Lagadic Group, Inria/Irisa, 35042, Rennes, France

    François Chaumette

  2. Department of Electrical and Computer Engineering, University of Illinois, 1308 West Main Street, IL 61801, Urbana-Champaign, USA

    Seth Hutchinson

  3. Department of Electrical Engineering and Computer Science, Queensland University of Technology, 2 George Street, QLD 4001, Brisbane, Australia

    Peter Corke

Authors
  1. François Chaumette
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  2. Seth Hutchinson
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  3. Peter Corke
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Corresponding author

Correspondence to François Chaumette .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy

    Bruno Siciliano

  2. Department of Computer Sciences, Artificial Intelligence Laboratory, Stanford University, 450 Serra Mall, CA 94305, Stanford, USA

    Oussama Khatib

Video-References

Video-References

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IBVS on a 6 DOF robot arm (1); available from http://handbookofrobotics.org/view-chapter/34/videodetails/59

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IBVS on a 6 DOF robot arm (2); available from http://handbookofrobotics.org/view-chapter/34/videodetails/60

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IBVS on a 6 DOF robot arm (3); available from http://handbookofrobotics.org/view-chapter/34/videodetails/61

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PBVS on a 6 DOF robot arm (1); available from http://handbookofrobotics.org/view-chapter/34/videodetails/62

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PBVS on a 6 DOF robot arm (2); available from http://handbookofrobotics.org/view-chapter/34/videodetails/63

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2.5-D VS on a 6 DOF robot arm (1); available from http://handbookofrobotics.org/view-chapter/34/videodetails/64

:

2.5-D VS on a 6 DOF robot arm (2); available from http://handbookofrobotics.org/view-chapter/34/videodetails/65

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Chaumette, F., Hutchinson, S., Corke, P. (2016). Visual Servoing. In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-32552-1_34

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  • DOI: https://doi.org/10.1007/978-3-319-32552-1_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32550-7

  • Online ISBN: 978-3-319-32552-1

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