grasping 3d grasp quality computations

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Grasping 3D Grasp Quality Computations B659: Principles of Intelligent Robot Motion Spring 2013 David Tidd

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Grasping 3D Grasp Quality Computations. B659: Principles of Intelligent Robot Motion Spring 2013 David Tidd. Grasp Quality. Given two different grasps, how can they be compared? Are they stable? -> Force closure How stable are they? -> Grasp quality metrics. c 1. c 1. c 3. c 3. c 2. - PowerPoint PPT Presentation

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Page 1: Grasping 3D Grasp Quality Computations

Grasping3D Grasp Quality Computations

B659: Principles of Intelligent Robot Motion

Spring 2013David Tidd

Page 2: Grasping 3D Grasp Quality Computations

Grasp Quality

• Given two different grasps, how can they be compared?– Are they stable? -> Force closure– How stable are they? -> Grasp quality metrics

c1

c2c3

c1

c3

Page 3: Grasping 3D Grasp Quality Computations

Agenda

• Point force generalization• Wrench space• Grasp quality metrics• Simulation method

Page 4: Grasping 3D Grasp Quality Computations

Contact Types• Type of contact determined by colliding geometries– Point: point on plane (stable), point on point or line

(unstable)– Line: line on plane or nonparallel line (stable), line on

parallel line (unstable)– Plane: plane on plane

• Unstable contacts ignored in analysis

Point-PlanePoint-Point

Point-Line

Page 5: Grasping 3D Grasp Quality Computations

Everything as a Point Contact

• Line contact -> 2 points• Plane contact -> convex hull of points• Any distribution of normal forces across a region can

be represented as a weighted sum of point forces along that region’s convex hull

Page 6: Grasping 3D Grasp Quality Computations

Point Contacts with Coulomb Friction

• A point contact with friction is able to apply more than just a normal force

• “Friction cone” is the vector space of all possible forces a point can apply due to friction

• f = fn+ ft where |ft| ≤ |μs*fn|

nn

Page 7: Grasping 3D Grasp Quality Computations

Approximating Friction Cones

• Pyramidal approximation converts vector space to finite set of vectors– 8-sided approximation used in simulation

Page 8: Grasping 3D Grasp Quality Computations

Wrenches

• Each point force also applies torque– τ = d x f

• Wrench is a force-torque pair

– The i-th point contact has m wrenches, one for each force in the pyramidal approximation

– d is the vector from the point contact to the torque origin– λ is a constant relating force to torque for analysis

• λ = 1/r was chosen to make torque size invariant

Page 9: Grasping 3D Grasp Quality Computations

Wrench Space

• For 3D objects, wrench space is 6D– 3D for force, 3D for torque– For 2D objects, it’s 3D

fy

fx

τz

Page 10: Grasping 3D Grasp Quality Computations

Wrench Hulls

• Set of wrenches from ONE point contact = boundary of what wrenches can be applied from that one point

• Set of wrenches from ALL point contacts = convex hull in wrench space, total possible range of wrenches that can be applied

Page 11: Grasping 3D Grasp Quality Computations

2D Example

c1

c2

f1,1 f1,2f2,1 f2,2

d1

d2

COM

Is this grasp stable?

Page 12: Grasping 3D Grasp Quality Computations

2D Example

c1

c2

f1,1 f1,2f2,1 f2,2

d1

d2

COM

• 2 point contacts• 4 wrenches• Force closure?– Yes

• What about torque?• Direction of d x f– All torque is in same

direction, out of page

Page 13: Grasping 3D Grasp Quality Computations

2D Example

c1

c2

f1,1 f1,2f2,1 f2,2

d1

d2

COM

• Ignore fx for now

-fy +fy

τout

τin

w1,1

w1,2

w2,2

w2,1

Wrench hull

Does not contain origin, not stable

Page 14: Grasping 3D Grasp Quality Computations

2D Example

c1

c2

f1,1 f1,2

f2,1 f2,2

d1

d2

COM

• What if there was a 3rd point?

-fy +fy

τout

τin

w1,1

w1,2

w2,2

w2,1

Wrench hull

Does contain origin, stable

c3

f3,1 f3,2

d3

w3,2

w3,1

Page 15: Grasping 3D Grasp Quality Computations

Grasp Quality

• Both of these grasps are stable– But how stable are they?

c1

f1,1 f1,2

d1

COM

c3

f3,1 f3,2

d3

c1

c2

f1,1 f1,2

f2,1 f2,2

d1

d2

COM

c3

f3,1 f3,2

d3

Page 16: Grasping 3D Grasp Quality Computations

Grasp Quality Metrics

• Quality is how well a grip can resist disturbances• Worst case scenario– How efficiently can a grip resist disturbance wrenches at

its weakest point?• Weakest means the direction (in wrench space) at

which the sum normal force is converted to the desired wrench least efficiently– Grip a pencil at the end and try to resist torque– Now try it while gripping the center– The center requires much more normal force to get the

same wrench

Page 17: Grasping 3D Grasp Quality Computations

Worst Case Scenario

-fy

τout

τin

w1,1

w1,2

w2,2

w2,1

Hard to resist

w3,2

w3,1

• The point on the wrench hull that is closest to the origin is the weakest point

• Disturbances in the opposite direction are hardest to resist

• Metric ε = The radius of the largest ball that can be enclosed in the wrench hull– Varies from 0 to 1 due to

normalization of wrenches

+fy

ε

Page 18: Grasping 3D Grasp Quality Computations

Physical Meaning of ε

• In the worst case, the sum magnitude of the contact wrenches would need to be 1/ε times the disturbance wrench

Page 19: Grasping 3D Grasp Quality Computations

Grasp Quality Metrics

-fy

τout

τin

w1,1

w1,2

w3,2

w3,1

• So are these equal?

+fy

ε

-fy

τout

τin

w1,1

w1,2

w2,2

w2,1

w3,2

w3,1

+fy

ε

Page 20: Grasping 3D Grasp Quality Computations

Average Case Scenario

• How efficiently can a grip resist a disturbance wrench on average?

• Metric ν = Volume of the convex hull in wrench space

• The three point contact has more volume, so it is more stable on average

Page 21: Grasping 3D Grasp Quality Computations

Grasp Simulation Method

• Set hand configuration except for distal links• Iterate configuration of distal links and check for

collisions with object• Continue until all links have collided

Only one solution found. There could be better solutions. How to determine

initial configuration?

Page 22: Grasping 3D Grasp Quality Computations

Grasp Analysis Method

• Decompose the collisions into point contacts• Covert point contacts into sets of wrenches• Construct wrench hull• Compute quality metrics

Page 23: Grasping 3D Grasp Quality Computations

Grasp Search

• Each hand configuration maps to one grasp via simulation

• The total possible grasp space is equivalent to the initial configuration space of the hand

• Explore a subset of C-space using finite steps• Other methods?

Page 24: Grasping 3D Grasp Quality Computations

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