Lecture 6.3 Optimizing over poses

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Transcript of Lecture 6.3 Optimizing over poses

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Lecture 6.3 Optimizing over poses

Trym Vegard Haavardsholm

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Nonlinear state estimation

We have seen how we can find the MAP estimate of our unknown states given measurements by representing it as a nonlinear least squares problem

2olve argminS∗ ← −Δ

Δ AΔ b

, Linearize at tX←A b

1t tX X+ ∗← +Δ2

0Choose a suitable inital estimate X

2

1argmin ( )

i

m

i i iX i

X h X∗

=

= −∑ Σz

argmax ( | )MAP

XX p X Z=

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The indirect tracking method

3

2argmin ( )

cw

wcw cw i i

iπ∗ = −∑

TT T x u

Minimize geometric error over the camera pose

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Rotations and poses are Lie groups

Rotations in 3D: Poses in 3D:

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Rotations and poses are Lie groups

Rotations in 3D: Poses in 3D:

Rotations and poses are not vector spaces! (They lie on manifolds)

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Nonlinear state estimation

We have seen how we can find the MAP estimate of our unknown states give measurements by representing it as a nonlinear least squares problem

2olve argminS∗ ← −Δ

Δ AΔ b

, Linearize at tX←A b

1t tX X+ ∗← +Δ6

0Choose a suitable inital estimate X

2

1argmin ( )

i

m

i i iX i

X h X∗

=

= −∑ Σz

argmax ( | )MAP

XX p X Z=

Rotations and poses are not vector spaces! (They lie on manifolds) How do we optimize?

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The corresponding Lie algebra

Rotations in 3D:

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The corresponding Lie algebra

Rotations in 3D: Remember the axis-angle representation:

𝜙𝜙

𝐯𝐯

( )cos 1 cos sinTab φ φ φ ∧= + − +R I vv v

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The corresponding Lie algebra

Rotations in 3D: Remember the axis-angle representation:

( )cos 1 cos sinTab φ φ φ ∧= + − +R I vv v 𝜙𝜙

𝐯𝐯 When 𝜙𝜙 is small: cos 𝜙𝜙 ≈ 1 sin 𝜙𝜙 ≈ 𝜙𝜙

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( )cos 1 cos sinTab φ φ φ

φ

∧ ∧

= + − +

≈ + = +

R I vv v

I v I ω

The corresponding Lie algebra

Rotations in 3D: Remember the axis-angle representation:

𝜙𝜙

𝐯𝐯 When 𝜙𝜙 is small: cos 𝜙𝜙 ≈ 1 sin 𝜙𝜙 ≈ 𝜙𝜙

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The corresponding Lie algebra

Rotations in 3D: Poses in 3D:

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The corresponding Lie algebra

Rotations in 3D: Poses in 3D:

The corresponding Lie algebras

are vector spaces!

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We can relate the group and algebra through the matrix exponential and matrix logarithm

Relation between group and algebra

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We can relate the group and algebra through the matrix exponential and matrix logarithm

Relation between group and algebra

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Tangent space

The Lie algebra is the tangent space around the identity element of the group • The tangent space is the “optimal” space

in which to represent differential quantities related to the group

• The tangent space is a vector space with the same dimension as the number of degrees of freedom of the group transformations

Dellaert, F., & Kaess, M. (2017). Factor Graphs for Robot Perception

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Perturbations

We can represent steps and uncertainty as perturbations in the tangent space

exp( )∧=T ξ T

exp( )∧=R ω R

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Jacobians for perturbations on SO(3)

( )exp( )[ ]

∧∧

=

∂ ⊕= − ⊕

∂ω 0

ω R xR x

ω

( )exp( )∧∂ ⊕ ∂ ⊕= =

∂ ∂

ω R x R x Rx x

⊕ =R x RxGroup action on points:

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Jacobians for perturbations on SE(3)

( )3 3

exp( )[ ]

∧∧

×

=

∂ ⊕ = − ⊕ ∂

ξ 0

ξ T xI T x

ξ

( )exp( )∧∂ ⊕ ∂ ⊕= =

∂ ∂

ξ T x T x Rx x

⊕ = +T x Rx tGroup action on points:

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Summary

• Updates on rotations and poses as perturbations using Lie algebra

• Jacobians for these perturbations

• We are ready to solve

19

exp( )∧=R ω R

exp( )∧=T ξ T

2argmin ( )

cw

wcw cw i i

iπ∗ = −∑

TT T x u

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Supplementary material

• Ethan Eade, “Lie Groups for 2D and 3D transformations” • José Luis Blanco Claraco, “A tutorial on SE(3) transformation

parameterizations and on-manifold optimization”

Chapter 7