Canonical Graphs

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IncrementalInference.generateGraph_Kaess — Function

generateGraph_Kaess(; graphinit)

Canonical example from literature, Kaess, et al.: ISAM2, IJRR, 2011.

Notes

Paper variable ordering: p = [:l1;:l2;:x1;:x2;:x3]

IncrementalInference.generateGraph_TestSymbolic — Function

generateGraph_TestSymbolic(; graphinit)

Canonical example introduced by Borglab.

Notes

Known variable ordering: p = [:x1; :l3; :l1; :x5; :x2; :l2; :x4; :x3]

IncrementalInference.generateGraph_CaesarRing1D — Function

generateGraph_CaesarRing1D(; graphinit)

Canonical example introduced originally as Caesar Hex Example.

Notes

Paper variable ordering: p = [:x0;:x2;:x4;:x6;:x1;:l1;:x5;:x3;]

IncrementalInference.generateGraph_LineStep — Function

generateGraph_LineStep(lineLength; poseEvery, landmarkEvery, posePriorsAt, landmarkPriorsAt, sightDistance, vardims, noisy, graphinit, σ_pose_prior, σ_lm_prior, σ_pose_pose, σ_pose_lm, solverParams)

Continuous, linear scalar and multivariate test graph generation. Follows a line with the pose id equal to the ground truth.

IncrementalInference.generateGraph_EuclidDistance — Function

generateGraph_EuclidDistance()
generateGraph_EuclidDistance(points; dist, σ_prior, σ_dist, N, graphinit)

Generate a EuclidDistance test graph where 1 landmark position is unknown.

RoME.generateGraph_Circle — Function

generateGraph_Circle()
generateGraph_Circle(poses; fg, offsetPoses, autoinit, graphinit, landmark, loopClosure, stopEarly, biasTurn, kappaOdo, cyclePoses)

Generate a canonical factor graph: driving in a circular pattern with one landmark.

Notes

Poses, :x0, :x1,... Pose2,
Odometry, :x0x1f1, etc., Pose2Pose2 (Gaussian)
OPTIONAL: 1 Landmark, :l1, Point2,
2 Sightings, :x0l1f1, :x6l1f1, RangeBearing (Gaussian)

Example

using RoME

fg = generateGraph_Hexagonal()
drawGraph(fg, show=true)

DevNotes

TODO refactor to use new calcHelix_T.

generateGraph_Circle, generateGraph_Kaess, generateGraph_TwoPoseOdo

RoME.generateGraph_ZeroPose — Function

generateGraph_ZeroPose(; varType, graphinit, solverParams, dfg, doRef, useMsgLikelihoods, label, priorType, μ0, Σ0, priorArgs, solvable, variableTags, factorTags, postpose_cb)

Generate a canonical factor graph with a Pose2 :x0 and MvNormal with covariance P0.

Notes

Use e.g. varType=Point2 to change from the default variable type Pose2.
Use priorArgs::Tuple to override the default input arguments to priorType.
Use callback postpose_cb(g::AbstractDFG,lastpose::Symbol) to call user operations after each pose step.

RoME.generateGraph_Hexagonal — Function

generateGraph_Hexagonal(; fg, landmark, loopClosure, N, autoinit, graphinit)

Generate a canonical factor graph: driving in a hexagonal circular pattern with one landmark.

Notes

7 Poses, :x0-:x6, Pose2,
1 Landmark, :l1, Point2,
6 Odometry, :x0x1f1, etc., Pose2Pose2 (Gaussian)
2 Sightings, :x0l1f1, :x6l1f1, RangeBearing (Gaussian)

Example

using RoME

fg = generateGraph_Hexagonal()
drawGraph(fg, show=true)

generateGraph_Circle, generateGraph_Kaess, generateGraph_TwoPoseOdo, generateGraph_Boxes2D!

RoME.generateGraph_Beehive! — Function

generateGraph_Beehive!()
generateGraph_Beehive!(poseCountTarget; graphinit, dfg, useMsgLikelihoods, solvable, refKey, addLandmarks, landmarkSolvable, poseRegex, pose0, yaw0, μ0, postpose_cb, locality, atol)

Pretend a bee is walking in a hive where each step (pose) follows one edge of an imaginary honeycomb lattice, and at after each step a new direction left or right is stochastically chosen and the process repeats.

Notes

The keyword locality=1 is a positive ::Real ∈ [0,∞) value, where higher numbers imply direction decisions are more sticky for multiple steps.
Use keyword callback function postpose_cb = (fg, lastpose) -> ... to hook in your own features right after each new pose step.

DevNotes

TODO rewrite as a recursive generator function instead.

Missing docstring.

Missing docstring for RoME.generateGraph_Honeycomb!. Check Documenter's build log for details.

RoME.generateGraph_Helix2D! — Function

generateGraph_Helix2D!()
generateGraph_Helix2D!(numposes; posesperturn, graphinit, useMsgLikelihoods, solverParams, dfg, radius, spine_t, xr_t, yr_t, poseRegex, μ0, refKey, Qd, postpose_cb)

Generalized canonical graph generator function for helix patterns.

Notes

assumes poses are labeled according to r"x\d+"
Gradient (i.e. angle) calculations are on the order of 1e-8.
Use callback spine_t(t)::Complex to modify how the helix pattern is moved in x, y along the progression of t,
- See related wrapper functions for convenient generators of helix patterns in 2D,
- Real valued xr_t(t) and yr_t(t) can be modified (and will override) complex valued spine_t instead.
use postpose_cb = (fg_, lastestpose) -> ... for additional user features after each new pose
can be used to grow a graph with repeated calls, but keyword parameters are assumed identical between calls.

RoME.generateGraph_Helix2DSlew! — Function

generateGraph_Helix2DSlew!()
generateGraph_Helix2DSlew!(numposes; slew_x, slew_y, spine_t, kwargs...)

Generate canonical slewed helix graph (like a flattened slinky).

Notes

Use slew_x and slew_y to pull the "slinky" out in different directions at constant rate.
See generalized helix generator for more details.
Defaults are choosen to slew along x and have multple trajectory intersects between consecutive loops of the helix.

generateGraph_Helix2D!, generateGraph_Helix2DSpiral!

RoME.generateGraph_Helix2DSpiral! — Function

generateGraph_Helix2DSpiral!()
generateGraph_Helix2DSpiral!(numposes; rate_r, rate_a, spine_t, kwargs...)

Generate canonical helix graph that expands along a spiral pattern, analogous flower petals.

Notes

This function wraps the complex spine_t(t) function to generate the spiral pattern.
- rate_a and rate_r can be varied for different spiral behavior.
See generalized helix generator for more details.
Defaults are choosen to slewto have multple trajectory intersects between consecutive loops of the helix and do a decent job of moving around coverage area with a relative balance of encircled area sizes.

generateGraph_Helix2D!, generateGraph_Helix2DSlew!