Model independent visual servoing
1 / 23

Model Independent Visual Servoing - PowerPoint PPT Presentation

  • Uploaded on

Model Independent Visual Servoing. CMPUT 610 Literature Reading Presentation Zhen Deng. Introduction . Summaries and Comparisons of Traditional Visual Servoing and Model independent Visual Servoing emphasizing on the latter.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' Model Independent Visual Servoing' - lynn-nelson

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Model independent visual servoing

Model Independent Visual Servoing

CMPUT 610 Literature Reading Presentation

Zhen Deng


  • Summaries and Comparisons of Traditional Visual Servoing and Model independent Visual Servoing emphasizing on the latter.

  • Works are mostly from Jenelle A. Piepmeier’s thesis and Alexandra Hauck’s thesis

Visual servo
Visual Servo

  • Visual servo control has the potential to provide a low-cost, low-maintenance automation solution for unstructured industries and environments.

  • Robotics has thrived in ordered domains, it has found challenges in environments that are not well defined.

Traditional visual servoing
Traditional Visual Servoing

  • Precise knowledge of the robot kinematics, the camera model, or the geometric relationship between the camera and the robot systems is assumed.

  • Need to know the exact position of the end-effector and the target in the Cartesian Space.

  • Require lots of calculation.

Forward kinematics
Forward Kinematics

  • The Denavit-Hartenberg Notation:

    i-1 T i = Rotz(q) . Transz(d) . Rotx(a) . Trans(a)

  • Transformation

    0 T e=0 T 11 T 22 T 3 … n-1 T n n T e

Jacobian by differential
Jacobian by Differential

  • Velocity variables can transformed between joint space and Euclidean space using Jacobian matrices

  • Dx = J * Dq

  • Dq = J \ Dx

  • Jij = ¶qi/ ¶xj

Model independent visual servoing1
Model Independent Visual Servoing

  • An image-based Visual Servoing method.

  • Could be further classified as dynamic look-and-move according to the classification scheme developed by Sanderson and Weiss.

  • Estimate the Jacobian on-line and does not require calibrated models of either of the camera configuration or the robot kinematics.


  • Martin Jagersand formulates the visual Servoing problem as a nonlinear least squares problem solved by a quasi-Newton method using Broyden Jacobian estimation.

  • Base on Martin’s work, Jenelle P adds a frame to solve the problem of grasping a moving target.

  • me ? …

Reaching a stationary target
Reaching a Stationary Target

  • Residual error f(q) = y(q) - y*.

  • Goal: minimize f(q)

  • Df = fk - fk-1

  • Jk = Jk-1 + (Df-Jk-1Dq) DqT/ DqTDq

  • qk+1 = qk -J-1kfk

Tracking the moving object
Tracking the moving object

  • Interaction with a moving object, e.g. catching or hitting it, is perhaps the most difficult task for a hand-eye system.

  • Most successful systems presented in paper uses precisely calibrated, stationary stereo camera systems and image-processing hardware together with a simplified visual environment.

Peter k allen s work
Peter K. Allen’s Work

  • Allen et al. Developed a system that could grasp a toy train moving in a plain. The train’s position is estimated from(hardware-supported) measurements of optic flow with a stationary,calibrated stereo system.

  • Using a non-linear filtering and prediction, the robot tracks the train and finally grasps it.

Ball player
“Ball player”

  • Andersson’s ping-pong player is one of the earliest “ball playing” robot.

  • Nakai et al developed a robotic volleyball player.

Jenelle s modification to broyden
Jenelle’s modification to Broyden

  • Residual error f(q,t) = y(q) - y*(t).

  • Goal: minimize f(q,t)

  • Df = fk - fk-1

  • Jk = Jk-1 + (Df - Jk-1Dq + (¶ y*(t)/ ¶t *Dt) ) DqT/ DqTDq

  • qk+1 = qk -(JkTJk)-1 JkT (fk - (¶ y*(t)/ ¶t *Dt) ).


  • The residual error converges as the iterations increasing.

  • While the static method does not.

  • The mathematics proof of this result could be found in Jenelle’s paper.

Future work
Future work ?

  • Analysis between the two distinct ways of computing the Jacobian Matrix.

  • Solving the tracking problem without the knowledge of target motion.

  • More robust … ?

Literature links
Literature Links


  • A Dynamic Quasi-Newton Method for Uncalibrated Visual Servoing by Jenelle al

  • Automated Tracking and Grasping of a Moving Object with a Robotic Hand-Eye System. By Peter K. Allen


  • Model Independent approach is proved to be more robust and more efficient.