Potential Field Approach for Haptic Selection Jean Simard Mehdi - - PowerPoint PPT Presentation

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Potential Field Approach for Haptic Selection Jean Simard Mehdi - - PowerPoint PPT Presentation

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Potential Field Approach for Haptic Selection Jean Simard Mehdi Ammi Flavien Picon Patrick Bourdot jean.simard@limsi.fr CNRS LIMSI University of Paris XI Orsay, France Graphics Interface 2009 Kelowna, Canada Jean Simard (CNRS

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SLIDE 1

Potential Field Approach for Haptic Selection

Jean Simard Mehdi Ammi Flavien Picon Patrick Bourdot jean.simard@limsi.fr

CNRS — LIMSI University of Paris XI Orsay, France

Graphics Interface 2009 Kelowna, Canada

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 1 / 10

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SLIDE 2

Outline

1 Introduction

Haptic in CAD

2 Force model

The selection process Previous approach Proposed model

3 Potential field

From force model to potential field Combination of potential fields

4 Conclusion and perspectives

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 2 / 10

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SLIDE 3

Introduction Haptic in CAD

Haptic in CAD

Problem Complex CAD models 3d environment

2d visualisation 2d manipulation

Propositions 3d manipulation with 6 DoF interface Display informations on haptic modality

1 Feel the environment 2 Guide the user 3 Assist the user

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 3 / 10

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SLIDE 4

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-5
SLIDE 5

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-6
SLIDE 6

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-7
SLIDE 7

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-8
SLIDE 8

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-9
SLIDE 9

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-10
SLIDE 10

Force model The selection process

The selection process

Specifications

1 Reach the targets 2 Differentiate the elements 3 Feel in high density areas

1 1 2 3 −1 −2

x F

b

b

E ff e c t

  • r

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

slide-11
SLIDE 11

Force model Previous approach

Previous approach

Three force models by [?] based on [?] Square

x F σ φ ϕ

γ = 1

2

Linear

x F σ φ ϕ

γ = 1 Quadratic

x F σ φ ϕ

γ = 2 Definition of the force model F(x) =

  

φ ·

x

σ

γ

x ∈ [0, σ] φ ·

  • ϕ−x

ϕ−σ

γ

x ∈ [σ, ϕ]

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 5 / 10

slide-12
SLIDE 12

Force model Proposed model

Proposed model

Three proposed force models Square

x F σ φ

γ = 1

2

Linear

x F σ φ

γ = 1 Quadratic

x F σ φ

γ = 2 Definition of the proposed force model σ — Size of the active area φ — Maximum amplitude of the force F(x) = φ

x

σ

γ

exp

 γ

  • σ2 − x2

2σ2

 

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 6 / 10

slide-13
SLIDE 13

Potential field From force model to potential field

From force model to potential field

From the force model to the potential field inspired by [?] Force model

x F σ φ

γ = 1

F(x) = φ x σ

  • exp
  • σ2 − x 2

2σ2

  • Potential field

x U P

b

σ

U(X, P) = φ·σ exp

  • σ2 −

XP

2

2σ2

  • Force model to potential field

F(X, P) = −∇U(X, P)

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 7 / 10

slide-14
SLIDE 14

Potential field Combination of potential fields

Combination of potential fields

Example Combine the potential fields of two vertices of a cube x U

b b

A B

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-15
SLIDE 15

Potential field Combination of potential fields

Combination of potential fields

Example Put the potential field of a first vertex x U

b b

xA

U

A Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-16
SLIDE 16

Potential field Combination of potential fields

Combination of potential fields

Example Put the potential field of a second vertex x U

b b

xA

U

A

xB

U

B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-17
SLIDE 17

Potential field Combination of potential fields

Combination of potential fields

Example The local maxima indicate the emplacement of the vertex x U

b b

xA

U

A

xB

U

B

Local maxima

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

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SLIDE 18

Potential field Combination of potential fields

Combination of potential fields

Example Addition of the two potential fields x U

b b

xA

U

A

xB

U

B

U

A

+ U

B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-19
SLIDE 19

Potential field Combination of potential fields

Combination of potential fields

Example The local maxima implies unexpected haptic effect x U

b b

xA

U

A

xB

U

B

U

A

+ U

B

Unexpected local maxima

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-20
SLIDE 20

Potential field Combination of potential fields

Combination of potential fields

Example Return to the potential fields of the two vertices x U

b b

xA

U

A

xB

U

B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-21
SLIDE 21

Potential field Combination of potential fields

Combination of potential fields

Example Apply the max function x U

b b

xA

U

A

xB

U

B

max {U

A

, U

B

}

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-22
SLIDE 22

Potential field Combination of potential fields

Combination of potential fields

Example The two local maxima are preserved x U

b b

xA

U

A

xB

U

B

Local maxima

max {U

A

, U

B

}

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

slide-23
SLIDE 23

Conclusion and perspectives

Conclusion and perspectives

Force model

x F σ φ

b

Potential field

x U P

b

σ

Combination of potential fields with max x U xA xA xB

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 9 / 10

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SLIDE 24

Conclusion and perspectives

Potential Field Approach for Haptic Selection

Jean Simard Mehdi Ammi Flavien Picon Patrick Bourdot jean.simard@limsi.fr

CNRS — LIMSI University of Paris XI Orsay, France

Graphics Interface 2009 Kelowna, Canada

Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 10 / 10