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Commit 7d71b379 authored by cont-integration's avatar cont-integration
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[skip ci] yaml templates added or modified

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dynamic: false # DOC If the orientation is dynamic, i.e. it changes along time. - TYPE bool
value: [0.0, 0.0, 0.0, 0.0] # DOC A vector containing the quaternion values (x, y, z, w) - TYPE Vector4d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [rad]. - TYPE Vector3d
drift_std: [0.0, 0.0, 0.0] # OPTIONAL - DOC A vector containing the stdev values of the noise of the drift factor per second (only if dynamic==true), i.e. the sqrt of the diagonal elements of the covariance matrix [rad/sqrt(s)]. - TYPE Vector3d
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dynamic: false # DOC If the position is dynamic, i.e. it changes along time. - TYPE bool
value: [0.0, 0.0] # DOC A vector containing the position (x, y) [m]. - TYPE Vector2d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [m]. - TYPE Vector2d
drift_std: [0.0, 0.0] # OPTIONAL - DOC A vector containing the stdev values of the noise of the drift factor per second (only if dynamic==true) i.e. the sqrt of the diagonal elements of the covariance matrix [m/sqrt(s)]. - TYPE Vector2d
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dynamic: false # DOC If the position is dynamic, i.e. it changes along time. - TYPE bool
value: [0.0, 0.0, 0.0] # DOC A vector containing the position (x, y, z) [m]. - TYPE Vector3d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [m]. - TYPE Vector3d
drift_std: [0.0, 0.0, 0.0] # OPTIONAL - DOC A vector containing the stdev values of the noise of the drift factor per second (only if dynamic==true) i.e. the sqrt of the diagonal elements of the covariance matrix [m/sqrt(s)]. - TYPE Vector3d
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period: 0.0 # DOC Period of the solver thread. - TYPE double
verbose: 0 # DOC Verbosity of the solver. 0: Nothing, 1: Brief report, 2: Full report. - TYPE int - OPTIONS [0, 1, 2]
compute_cov: false # DOC If the solver has to compute any covariance matrix block. - TYPE bool
cov_enum: 0 # MANDATORY if $compute_cov - DOC Which covariance matrix blocks have to be computed. 0: All blocks and all cross-covariances. 1: All marginals. 2: Marginals of landmarks and current robot pose plus cross covariances of current robot and all landmarks. 3: Last frame P and V. 4: Last frame P, O, V and T. 5: Last frame P and T. - TYPE int - OPTIONS [0, 1, 2, 3, 4, 5]
cov_period: 0.0 # MANDATORY if $compute_cov - DOC Period of the covariance computation. - TYPE double
minimizer: "LEVENBERG_MARQUARDT" # DOC Type of minimizer. - TYPE string - OPTIONS [LEVENBERG_MARQUARDT, levenberg_marquardt, DOGLEG, dogleg, LBFGS, lbfgs, BFGS, bfgs]
interrupt_on_problem_change: false # DOC If the solver has to interrupted each time the problem changes to rebuild the problem. - TYPE bool
min_num_iterations: 0 # MANDATORY if $interrupt_on_problem_change - DOC Amount of solver iterations during which the solver cannot be interrupted (used in interrupt_on_problem_change == true). - TYPE unsigned int
max_num_iterations: 0 # DOC Maximum amount of solver iterations. If the solver didn"t converge after this amount of iterations, it stops anyway. - TYPE unsigned int
function_tolerance: 0.0 # DOC Function tolerance. Convergence criterion. Typical value: 1e-8 - TYPE double
gradient_tolerance: 0.0 # DOC Gradient tolerance. Convergence criterion. Typical value: 1e-8 - TYPE double
n_threads: 1 # DOC Amount of threads used by ceres. - TYPE unsigned int - OPTIONS [1, 2, 3, 4]
use_nonmonotonic_steps: false # OPTIONAL - DOC If the solver is allowed to update the solution with non-monotonic steps. Only used in LEVENBERG_MARQUARDT and DOGLEG minimizers. - TYPE bool
max_consecutive_nonmonotonic_steps: 2 # OPTIONAL - DOC Amount of consecutive non-monotonic steps allowed. Only used in LEVENBERG_MARQUARDT and DOGLEG minimizers. - TYPE unsigned int
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period: 0.0 # DOC Period of the solver thread. - TYPE double
verbose: 0 # DOC Verbosity of the solver. 0: Nothing, 1: Brief report, 2: Full report. - TYPE int - OPTIONS [0, 1, 2]
compute_cov: false # DOC If the solver has to compute any covariance matrix block. - TYPE bool
cov_enum: 0 # MANDATORY if $compute_cov - DOC Which covariance matrix blocks have to be computed. 0: All blocks and all cross-covariances. 1: All marginals. 2: Marginals of landmarks and current robot pose plus cross covariances of current robot and all landmarks. 3: Last frame P and V. 4: Last frame P, O, V and T. 5: Last frame P and T. - TYPE int - OPTIONS [0, 1, 2, 3, 4, 5]
cov_period: 0.0 # MANDATORY if $compute_cov - DOC Period of the covariance computation. - TYPE double
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value: [0.0] # DOC A vector containing the orientation, yaw [rad]. - TYPE Vector1d
prior:
mode: "fix" # DOC It can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [rad]. - TYPE Vector1d
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value: [0.0, 0.0, 0.0, 0.0] # DOC A vector containing the quaternion values (x, y, z, w) - TYPE Vector4d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [rad]. - TYPE Vector3d
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value: [0.0, 0.0] # DOC A vector containing the position (x, y) [m]. - TYPE Vector2d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [m]. - TYPE Vector2d
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value: [0.0, 0.0, 0.0] # DOC A vector containing the position (x, y, z) [m]. - TYPE Vector3d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix [m]. - TYPE Vector3d
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value: [0.0] # DOC A vector containing the state value. - TYPE Vector1d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector1d
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value: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector10d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector10d
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value: [0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector2d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector2d
\ No newline at end of file
value: [0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector3d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector3d
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value: [0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector4d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector4d
\ No newline at end of file
value: [0.0, 0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector5d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector5d
\ No newline at end of file
value: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector6d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector6d
\ No newline at end of file
value: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector7d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector7d
\ No newline at end of file
value: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector8d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector8d
\ No newline at end of file
value: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # DOC A vector containing the state values. - TYPE Vector9d
prior:
mode: "fix" # DOC Can be "factor" to add an absolute factor (with covariance defined in "factor_std"), "fix" to set the values constant or "initial_guess" to just set the values. - TYPE string - OPTIONS [fix, factor, initial_guess]
factor_std: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # MANDATORY if $mode == "factor" - DOC A vector containing the stdev values of the noise of the factor, i.e. the sqrt of the diagonal elements of the covariance matrix. - TYPE Vector9d
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type: "whatever" # DOC Type of the TreeManager. To keep all frames, use \none\. - TYPE string
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