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Hybrid Manipulation: Force-Vision

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Title: Hybrid Manipulation: Force-Vision


1
Hybrid Manipulation Force-Vision
  • CMPUT 610
  • Martin Jagersand

2
Today
  • How to incorporate other sensory feedback.
  • Focus on tasks where the number of contact
    constraints increase during manipulations.
  • Acquire necessary constraint geometry on-line.

3
PreliminariesVisual Servoing Applications
4
Limitations of Visual Control
  • Accuracy is limited by Visual tracking
  • and Visual goal specification
  • (Jagersand et. al. ICRA 97)
  • Specifying well defined visual encodings can be
    difficult (Hager, Hespana, Dodds,
    Jagersand)
  • Limited to non-occluded settings
  • Not all tasks lend themselves to visual
    specification.

5
ObservationForce constraints natural in tasks
  • Example
  • Inserting a box
  • Sequence of motions
  • Increasing number of contact constraints

6
Preliminaries Uncalibrated Visual Servoing
  • Let y visual observation x motor control
  • Linear system model
  • y
  • Linear p-controller
  • Estimate the Visual-Motor Jacobian

7
What do we need to add to do things like this?
8
Learning Constraint Geometry
  • Impact force along surface normal
  • Sliding motion
  • 3rd vector

9
Constraint Frame
  • With force frame tool frame we get
  • Assume frictionless gt Can update each time step

P2
P1
P3
10
Hybrid Control Law
  • Let Q Joint -gt Tool Jacobian
  • Let S be a switching matrix, e.g. diag(0,1,1)
  • Velocity control u

Visual part
Force part
11
Accounting for Friction
  • Friction force is along motion direction!
  • Subtract out to recover surface normal

12
Final Hybrid Controller Structure
13
Motion Sequence
14
Switching of Constraints inHybrid Force-Vision
Feedback
15
Sliding along a Curved Surface
  • In principle any smooth surface can be followed

Detail of measured force
Estimated surface normals
16
Estimation Accuracy
  • The constraint coordinate frame was acquired
    within a few degrees of the true surface frame

17
Conclusions
  • Hybrid Force-Vision control allow more accurate
    positioning than vision or force alone
  • Many tasks naturally involve an increasing number
    of contact constraints
  • We showed that the contact geometry can be
    successfully estimated
  • Combined Uncalibrated Vision Force control
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