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Improving Method for Computation of Improving Method for Computation of Grasp Quality Metric Grasp Quality Metric Using Minimal Breaking Force on Objects Using Minimal Breaking Force on Objects Mana Borwornpadungkitti Advisor: Asst. Prof.

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Improving Method for Computation of Improving Method for Computation of Grasp Quality Metric Grasp Quality Metric Using Minimal Breaking Force on Objects Using Minimal Breaking Force on Objects

Mana Borwornpadungkitti Advisor: Asst. Prof. Nattee Niparnan, Ph.D.

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Outline

1) Introduction 2) Our Improvements 3) Evaluation 4) Conclusion

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Outline

1)Introduction

Background knowledge

Related works 2) Our Improvements

3) Evaluation 4) Conclusion

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Grasp Synthesis

Generate and test

Grasp quality measure

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Grasp Quality Measure

Robustness

Task

External disturbance resistance

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Outline

1) Introduction

Background knowledge

Related works 2) Our Improvements

3) Evaluation 4) Conclusion

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Wrench

  • force and torque

– R3 (R2 + R) in 2D – R6 (R3 + R3) in 3D

  • Wrench space - set of wrenches
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Useful Wrench Spaces

  • Grasp Wrench Space (GWS)
  • Object Wrench space (OWS)
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Useful Wrench Spaces

  • Grasp Wrench Space (GWS)

– Set of wrenches generated from unit contact forces of grasp

  • Object Wrench space (OWS)
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ε metric [Ferrari and Canny 92]

  • Magnitude of smallest wrench that the grasp cannot withstand
  • Minimum distance from origin to boundary of grasp wrench

space

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ε metric - drawbacks

  • Mixed force and torque unit
  • Depend on reference frame and scale
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Useful Wrench Spaces

  • Grasp Wrench Space (GWS)

– Set of wrenches generated from unit contact forces of grasp

  • Object Wrench space (OWS)

– Set of wrenches generated from distribution of unit forces

acting on object surface

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Object Wrench Space

Usually approximated

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Judge Grasp by its Contacts?

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GWS / OWS

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GWS / OWS

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GWS / OWS

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Minimum summation of magnitude of forces acting on the object that break the grasp

Propose

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Advantages

  • Using object as input
  • Force unit
  • Invariant of reference frame and scale
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Outline

1) Introduction

Background knowledge

Related works 2) Our Improvements

3) Evaluation 4) Conclusion

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Related Works

  • Borst et al.; ICRA04
  • Strandberg and Wahlberg; TRO06
  • Wen and Wu; JZUS-C12
  • Jeong and Cheong; ROB12
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Related Works

  • Borst et al.; ICRA04
  • Approximate OWS, incomplete
  • Strandberg and Wahlberg; TRO06
  • Wen and Wu; JZUS-C12
  • Jeong and Cheong; ROB12
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Related Works

  • Borst et al.; ICRA04
  • Approximate OWS, incomplete
  • Strandberg and Wahlberg; TRO06
  • Discretize force direction, incomplete
  • Wen and Wu; JZUS-C12
  • Jeong and Cheong; ROB12
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Related Works

  • Borst et al.; ICRA04
  • Approximate OWS, incomplete
  • Strandberg and Wahlberg; TRO06
  • Discretize force direction, incomplete
  • Wen and Wu; JZUS-C12
  • Ray shooting, faster and more complete
  • Jeong and Cheong; ROB12
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Related Works

  • Borst et al.; ICRA04
  • Approximate OWS, incomplete
  • Strandberg and Wahlberg; TRO06
  • Discretize force direction, incomplete
  • Wen and Wu; JZUS-C12
  • Ray shooting, faster and more complete
  • Jeong and Cheong; ROB12
  • Complete in simplifjed problem, slow
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Borst et al. ICRA04 Strandberg and Wahlberg TRO06 Jeong and Cheong ROB12 Wen and Wu JZUS-C12 Thesis

Timeline

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Minimal Breaking Force

  • Equivalent to maximum scale of OWS inside GWS

Scaled OWS OWS GWS

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[Strandberg and Wahlberg; TRO06]

  • Approximate OWS by Discretized force direction
  • Result in surface in force space
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[Wen and Wu; JZUS-C12]

  • Improvement to [Strandberg and Wahlberg; TRO06]
  • Use ray shooting to calculate GWS - OWS intersection
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Drawbacks

  • Slow
  • Inaccurate
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Drawback - slow

[Wen and Wu; JZUS-C12]

  • 2.69 sec; MATLAB on 3.16 GHz desktop computer
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Drawback - inaccurate

  • [Strandberg and Wahlberg; TRO06]
  • [Wen and Wu; JZUS-C12]
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Objective

  • Algorithm to calculate minimum force on object that break the

grasp

  • Input:

–

Grasp

–

Object model

  • Output:

–

Minimum breaking force (magnitude, position, and direction)

  • Speedup
  • Accuracy
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Outline

1) Introduction 2)Our Improvements

OWS fjlter

No discretized direction

3) Evaluation 4) Conclusion

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Our Improvements

Focus on

–

Efficiency

–

Accuracy

Two improvements

–

OWS filter

–

No discretized direction

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Our Improvements

Focus on

–

Efficiency

–

Accuracy

Two improvements

–

OWS filter

  • Efficiency only
  • Filtering criteria

–

No discretized direction

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Our Improvements

Focus on

–

Efficiency

–

Accuracy

Two improvements

–

OWS filter

  • Efficiency only
  • Filtering criteria

–

No discretized direction

  • Both efficiency and accuracy
  • Novel method
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Outline

1) Introduction 2) Our Improvements

OWS fjlter

No discretized direction

3) Evaluation 4) Conclusion

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Minimal Breaking Force

  • Is same as maximum scale of OWS inside GWS
  • Comes from single force
  • Acts on object vertex, for polyhedral object [Strandberg and Wahlberg; TRO06]
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Intersection point between minimum scaled compact set A and another compact convex set B is member of vertices of convex hull of A

  • A → OWS
  • B

→ GWS

vertex

A' A

B

Proposition

GWS

OWS'

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Improvement

Only vertices of convex hull of OWS instead of entire OWS 6 wrenches instead of 10 wrenches

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OWS filter - Complexity

O(|Vf| log m) per force direction

  • Vf : feasible vertices in this direction
  • m : number of vertices of convex hull

O(d|Vf| log m) overall

  • d

: number of force direction

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Outline

1) Introduction 2) Our Improvements

OWS fjlter

No discretized direction

3) Evaluation 4) Conclusion

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OWS Calculation

  • [Strandberg and Wahlberg 06]
  • [Wen and Wu 12]

Both discretize disturbance force direction

No discretized direction

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No Discretized Direction

  • Extended from [Strandberg and Wahlberg 06]
  • i : Force Direction
  • j : Vertex
  • k : hyperplane

concave

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Corollary

  • Optimal disturbance force direction for fixed object vertex and

GWS hyperplane

  • No discretized direction by iterating over all object vertex and

GWS hyperplane

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No Discretized Direction - Complexity

O(|V||H|)

  • V

: object vertices

  • H : GWS hyperplanes
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Outline

1) Introduction 2) Our Improvements 3)Evaluation

OWS fjlter

No discretized direction

4) Conclusion

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Evaluation

  • Compare our method with

–

[1] Strandberg and Wahlberg 06

–

[2] Wen and Wu 12

  • Octave on 3.16 GHz Core i7
  • Metrics

–

Speed

–

Accuracy

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Settings

  • μ

–

Robot: 0.3 (~ 16.7°)

–

Disturbance: 1.5 (~ 56.3°)

  • Friction cone approximated by 8-sided pyramid
  • Discretize direction using vertices of geodesic dome

–

freq = 1 to 9

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Objects - Basic

  • Box

: 6 facets

  • Sphere : 720 facets
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Objects - KIT

  • Three objects from KIT object models database
  • Three level of detail (# facet)
  • 800
  • 5k
  • 25k
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Grasps - Basic

  • Three grasps with different number of contact points

– Four – Five – Six

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Grasps - KIT

  • Three grasps using the BarrettHand in different parts of each object

– Bottom – Middle – Top

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Outline

1) Introduction 2) Our Improvements 3) Evaluation

OWS fjlter

No discretized direction

4) Conclusion

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0.267 0.223 0.654 0.538 0.538 1.09

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a b c d e f g h i

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  • SW [Strandberg and Wahlberg; TRO06]
  • WW [Wen and Wu; JZUS-C12]

Speedup - Basic

Object Grasp SW WW Box four 0.73 0.62 five 0.98 0.67 six 1.00 0.74 Sphere four 0.88 1.23 five 1.19 1.55 six 1.00 1.49

Speedup= T old T new

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  • SW [Strandberg and Wahlberg; TRO06]
  • WW [Wen and Wu; JZUS-C12]

Speedup - KIT

17.4 0.9 e

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Outline

1) Introduction 2) Our Improvements 3) Evaluation

OWS fjlter

No discretized direction

4) Conclusion

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No Discretized Direction

Black, green, and blue line represent BW, SW9, and SW3, respectively

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No Discretized Direction

Black, green, and blue line represent BW, SW9, and SW3, respectively

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No Discretized Direction

Black, green, and blue line represent BW, SW9, and SW3, respectively

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No Discretized Direction

Black, green, and blue line represent BW, SW9, and SW3, respectively

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No Discretized Direction

Black, green, and blue line represent BW, SW9, and SW3, respectively

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Outline

1) Introduction 2) Our Improvements 3) Evaluation 4)Conclusion

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Conclusion

  • Computation of a minimal magnitude of force acting on
  • bject that break the grasp
  • Speed up calculation time

– examining only vertices of convex hull of OWS

  • Improve accuracy

– calculating optimal disturbance force direction

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Publications

  • M. Borwornpadungkitti, W. Watcharawisetkul, N. Niparnan, A. Sudsang,

Improved Method for Computation of Grasp Quality Metric Using Minimal Breaking Force on Objects, in: 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2014.

  • M. Borwornpadungkitti, W. Watcharawisetkul, N. Niparnan, A. Sudsang, Exact

Calculation for Disturbance Force Rejection Grasp Quality Measure, in: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

  • W. Watcharawisetkul, M. Borwornpadungkitti, N. Niparnan, A. Sudsang, A

Randomized Approach in Identifying High Quality Force Closure Grasp from Contact Points in Real Time, in: Applied Mechanics and Materials, 2015.

  • W. Watcharawisetkul, M. Borwornpadungkitti, N. Niparnan, A. Sudsang, The

Quickgrasp Algorithm for Grasp Synthesis, in: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

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Thank you Thank you

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Force closure [Nguyen 88]

  • Ability to withstand external wrench in every direction
  • Zero wrench lies in the interior of grasp wrench space
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Disturbance force direction

normal only discretize no discretize

Friction cone

pyramid Jeong Cheong Strandberg Wahlberg Thesis exact Journal Wen Wu

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[Jeong and Cheong 12]

  • Similar to [Strandberg and Wahlberg 06]
  • Consider only forces normal to the object surface
  • Quantitative measurement results in scalar value
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Challenge

  • Complete solution is nonlinear

–

Pure convex optimization is slow [Jeong and Cheong, 2012]

–

Multivariate calculus

  • Ordering of surface point
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Consider every disturbance force on object

Judge Grasp by its Contacts?

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GWS vs OWS GWS vs OWS GWS vs OWS

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Related Works

  • Borst et al.; ICRA04
  • Strandberg and Wahlberg; TRO06
  • Jeong and Cheong; ROB12
  • Wen and Wu; JZUS-C12