ch24 in robotics handbook presented by wen li ph.d. student texas a&m university
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Visual Servoing and Target Tracking
CH24 in Robotics Handbook
Presented by Wen LiPh.D. student
Texas A&M University
Outline
Visual Servo Control Image based visual servo Position based visual servo Hybrid visual servo and other issues Target Tracking
Outline
Visual Servo Control Image based visual servo Position based visual servo Hybrid visual servo and other issues Target Tracking
Visual Servo Control
Vision Based Robot Control
Task: USE - computer vision data CONTROL - motion of a robot
Visual Servo Control
Basic Components Image features Error function Velocity controller Interaction matrix
Visual Servo Control
Basic Components Image features Error function Velocity controller Interaction matrix
s(m(t),a) ; a is a set of parameters that represent potential additional knowledge about the system (e.g. Camera intrinsic parameters); m(t) is a set of image measurements (e.g. Image coordinates of interest points)s* contains the desired values of the features.
Visual Servo Control
Basic Components Image features
Error function Velocity controller Interaction matrix
e(t)=s(m(t),a)-s*The aim of the control scheme is to minimize error e(t)At the desired pose, e(t)=0.
Visual Servo Control
Basic Components Image features Error function
Velocity controller Interaction matrix
The control law
vc – the spatial velocity of the camera, input to the robot controller
Problem: what is the form of Ls
Visual Servo Control
Basic Components Image features Error function Velocity controller
Interaction matrix
Ls is the interaction matrix, which describes the relationship between the time variation of s and the camera velocity vc. , Le=Ls
is the approximation of the pseudo-inverse of Ls.Problem: how to estimate -- according to different designs of s
Outline
Visual Servo Control Image based servo control Position based servo control Hybrid visual servo and other issues Target Tracking
Image Based Visual Servo (IBVS) Image features s(m(t),a)
Traditionally, s is defined by the image-plane coordinates of a set of points. s=x=(x,y)
(x,y)
Image Based Visual Servo (IBVS)
Interaction Matrix
The value Z is the depth of the point relative to the camera frame. Therefore, any control scheme that uses this form of the interaction matrix must estimate or approximate the value of Z.When Z is not known, cannot be directly used. An approximation must be used.
To control six degrees of freedom, at least three points are necessary. There exists some configurations for which Lx is singular.
Image Based Visual Servo (IBVS)
Advantages: The positioning accuracy of the system
is less sensitive to camera calibration errors
Computational advantageDisadvantages:
Presence of singularityServoing in 2-D
Outline
Visual Servo Control Image based servo control Position based servo control Hybrid visual servo and other issues Target Tracking
Position Based Visual Servo (PBVS)
extract the image features -> compute the current camera pose with respect to
a reference coordinate on the object -> compare with the desired camera pose with
respect to the reference coordinate on the object
Current pose
desired pose
x
yz
Position Based Visual Servo (PBVS)
Consider three coordinate frames: The current camera frame The desired camera frame A reference frame attached to the object gives the coordinates of the origin of the
object frame to the current camera frame gives the coordinates of the origin of the
object frame to the desired camera frame , the rotation matrix that gives the
orientation of the current camera frame relative to the desired frame
Position Based Visual Servo (PBVS)
Define s=(t,θu) t is a translation vector, θu is the
angle/axis parameterization for the rotation
1) t is defined relative to the object frame
Position Based Visual Servo (PBVS)
Define s=(t,θu) t is a translation vector, θu is the
angle/axis parameterization for the rotation
2) t is defined relative to the desired camera frame
Position Based Visual Servo (PBVS)
Advantages: Possible to describe tasks in terms
Cartesian pose as is common in RoboticsDisadvantages:
Sensitive to calibration error Depend on having an accurate mode of
target objects – a form of calibrationsServoing in 3-D
Outline
Visual Servo Control Image based servo control Position based servo control Hybrid servo and other issues Target Tracking
Hybrid servo and other extensions
Hybrid VS – combining 2-D and 3-D features 2.5-D visual servo – add depth of the
point
s▪ Camera trajectory is a straight line▪ Image trajectory of the center of the gravity
of the object is also a straight line
Hybrid servo and other issues
Stereo vision system in IBVS
Because of epipolar constraint, this approach actually requires 3-D parameters in s. Thus, it would be, strictly speaking, a position-based approach
Outline
Visual Servo Control Image based servo control Position based servo control Hybrid visual servo and other issues Target Tracking
Target Tracking
Moving target => varying value s*(t)
The time variation of e due to the generally unknown target motion
Estimate ∂e/∂t Improve estimated value using Kalman filter or more-elaborate filtering methods