Optimization over Manifolds with applications to Robotic Needle - - PowerPoint PPT Presentation

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Optimization over Manifolds with applications to Robotic Needle - - PowerPoint PPT Presentation

Optimization over Manifolds with applications to Robotic Needle Steering and Channel Layout Design Sachin Patil Guest Lecture: CS287 Advanced Robotics Trajectory Optimization Optimization over n vector spaces Not All State- Spaces are


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Optimization over Manifolds with applications to Robotic Needle Steering and Channel Layout Design

Sachin Patil Guest Lecture: CS287 Advanced Robotics

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Trajectory Optimization

Optimization over vector spaces

n

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Not All State-Spaces are ‘Nice’

  • Nonholonomic system cannot move in arbitrary directions in

its state space

  • For a simple car: Configuration space is in

(the SE(2) group)

2 1 : [ , , ]

x y  

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Nonholonomy Examples

Car pulling trailers:

2 1 1 1

  

Bicycle:

2 1 1

 

Rolling Ball: ?

2

(3) SO 

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C-Spaces as Manifolds

Manifold: Topological space that near each point resembles Euclidean space Other examples:

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Optimization over Manifolds

n

?

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Optimization over Manifolds

n

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Optimization over Manifolds

n

Define projection operator from tangent space to manifold

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Case Study: Rotation Group (SO(3))

3 3 

Optimization over SO(3) arises in robotics, graphics, vision etc. Rotation matrices:

  • Unique representation
  • ‘Smooth’
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: Incremental rotation to reference rotation defined in terms of axis-angle

Parameterization: Incremental Rotations

 Why not directly optimize over rotation matrix entries?

 Over-constrained (orthonormality)  Larger number of optimization variables

 Define local parameterization in terms of incremental rotation

r r

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Projection Operator

r

[ ]

e r

: Point on SO(3) that can be reached by traveling along the geodesic in direction

[ ]

e r

r [ ]

z y z x y x

  

      

r r r r r r

r

where

1

X k k

e X k

 



and is the matrix exponential operator

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Optimization Procedure

1) Seed trajectory: 2) Objective subject to: Constraints 3) Compute new trajectory: 4) Reset increments:

1

[ , , ]

i i i n

  r r

min

1

ˆ ˆ [ , , ]

i i i n

R R  

1

1 [ ] [ ] 1

ˆ ˆ [ · , , · ]

i i n

i i i n

R e R e

 

r r 1

[ , , ]

i 

r

[ ]

e r

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Steerable Needle

Steerable needle Target Bladder Prostate Pelvis Skin Cowper’s gland

Steerable needles inside phantom tissue Steerable needles navigate around sensitive structures (simulated)

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Steerable Needle

[Webster, Okamura, Cowan, Chirikjian, Goldberg, Alterovitz United States Patent 7,822,458. 2010]

Bevel-tip Highly flexible Reaction forces from tissue Follows constant curvature paths State (needle tip)

  • Position: 3D
  • Orientation: 3D

3

(3) : (3) SE SO 

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Steerable Needle: Opt Formulation

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Steerable Needle Plans

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Results

Why is minimizing twist important?

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Channel Layout (Brachytherapy Implants)

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Channel Layout: Opt Formulation

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Results

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 Optimization over manifolds – Generalization of optimization

  • ver Euclidean spaces

 Define incremental parameterization and projection

  • perators between tangent space and manifold

 Optimize over increments; reset after each SQP iteration!

Takeaways

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Parameterization: Euler Angles

Euler angles What problems do you foresee in directly using Euler angles in optimization?

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Parameterization: Euler Angles

 Topology not preserved:  Not unique, discontinuous  Gimbal lock

[0,2 ] [0,2 ] [0,2 ]     

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Parameterization: Axis-Angles

Orientation defined as rotation around axis

  • 3-vector; norm of vector

is the angle

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Parameterization: Axis-Angles

Distances are not preserved! Solution: Keep re-centering the axis-angle around a reference rotation (identity)