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

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

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

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

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

b b Force model The selection process The selection process F 1 x − 2 − 1 1 2 3 Specifications 1 Reach the targets 2 Differentiate the elements E ff e c 3 Feel in high density areas t o r Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 4 / 10

Force model Previous approach Previous approach Three force models by [ ? ] based on [ ? ] Square Linear Quadratic F F F γ = 1 γ = 1 γ = 2 φ φ φ 2 x x x σ ϕ σ ϕ σ ϕ Definition of the force model � x � γ  x ∈ [ 0 , σ ] φ · σ  F ( x ) = � γ � ϕ − x φ · x ∈ [ σ, ϕ ]  ϕ − σ Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 5 / 10

Force model Proposed model Proposed model Three proposed force models Square Linear Quadratic F F F γ = 1 γ = 1 γ = 2 φ φ φ 2 x x x σ σ σ Definition of the proposed force model σ — Size of the active area φ — Maximum amplitude of the force � σ 2 − x 2 �    γ � γ � x F ( x ) = φ exp  2 σ 2 σ Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 6 / 10

b 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 Potential field F U γ = 1 φ σ x x σ P �� σ 2 − x 2 � � 2 � σ 2 − � � � x XP � F ( x ) = φ exp U ( X , P ) = φ · σ exp 2 σ 2 σ 2 σ 2 Force model to potential field F ( X , P ) = −∇ U ( X , P ) Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 7 / 10

b b Potential field Combination of potential fields Combination of potential fields Example Combine the potential fields of two vertices of a cube U A B x Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example Put the potential field of a first vertex U U A x x A Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example Put the potential field of a second vertex U U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example The local maxima indicate the emplacement of the vertex U Local maxima U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example Addition of the two potential fields U B U + U A U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example The local maxima implies unexpected haptic effect U Unexpected local maxima B U + U A U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example Return to the potential fields of the two vertices U U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example Apply the max function U } , U B max { U A U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Potential field Combination of potential fields Combination of potential fields Example The two local maxima are preserved U Local maxima } , U B max { U A U A U B x x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 8 / 10

b b Conclusion and perspectives Conclusion and perspectives Force model Potential field U F φ σ x x P σ Combination of potential fields with max U x x A x A x B Jean Simard (CNRS — LIMSI) Potential field for Haptic Selection GI 2009 9 / 10

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