This is the following error that I'm getting:
cv_bridge exception: [rgb8] is a color format but [8UC1] is not so they must have the same OpenCV type, CV_8UC3, CV16UC1 ....
I've made the following changes in the files:
src/cfg/rovio.info
; You can partially override parameter set in this file by creating your own subset of parameter in a separate info-file and include it with: ; #include "/home/user/workspace/rovio/cfg/rovio_custom.info" Common { doVECalibration true; Should the camera-IMU extrinsics be calibrated online depthType 1; Type of depth parametrization (0: normal, 1: inverse depth, 2: log, 3: hyperbolic) verbose false; Is the verbose active } Camera0 { CalibrationFile ; Camera-Calibration file for intrinsics qCM_x 0.00666398307551; X-entry of IMU to Camera quaterion (Hamilton) qCM_y -0.0079168224269; Y-entry of IMU to Camera quaterion (Hamilton) qCM_z -0.701985972528; Z-entry of IMU to Camera quaterion (Hamilton) qCM_w 0.712115587266; W-entry of IMU to Camera quaterion (Hamilton) MrMC_x -0.0111674199187; X-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_y -0.0574640920022; Y-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_z 0.0207586947896; Z-entry of IMU to Camera vector (expressed in IMU CF) [m] } Camera1 { CalibrationFile ; Camera-Calibration file for intrinsics qCM_x 0.00151329637706; X-entry of IMU to Camera quaterion (Hamilton) qCM_y -0.0123329249764; Y-entry of IMU to Camera quaterion (Hamilton) qCM_z -0.702657352863; Z-entry of IMU to Camera quaterion (Hamilton) qCM_w 0.711419885414; W-entry of IMU to Camera quaterion (Hamilton) MrMC_x -0.0091929160801; X-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_y 0.0540646643676; Y-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_z 0.0190387660614; Z-entry of IMU to Camera vector (expressed in IMU CF) [m] } Init { State { pos_0 0; X-entry of initial position (world to IMU in world) [m] pos_1 0; Y-entry of initial position (world to IMU in world) [m] pos_2 0; Z-entry of initial position (world to IMU in world) [m] vel_0 0; X-entry of initial velocity (robocentric, IMU) [m/s] vel_1 0; Y-entry of initial velocity (robocentric, IMU) [m/s] vel_2 0; Z-entry of initial velocity (robocentric, IMU) [m/s] acb_0 0; X-entry of accelerometer bias [m/s^2] acb_1 0; Y-entry of accelerometer bias [m/s^2] acb_2 0; Z-entry of accelerometer bias [m/s^2] gyb_0 0; X-entry of gyroscope bias [rad/s] gyb_1 0; Y-entry of gyroscope bias [rad/s] gyb_2 0; Z-entry of gyroscope bias [rad/s] att_x 0; X-entry of initial attitude (IMU to world, Hamilton) att_y 0; Y-entry of initial attitude (IMU to world, Hamilton) att_z 0; Z-entry of initial attitude (IMU to world, Hamilton) att_w 1; W-entry of initial attitude (IMU to world, Hamilton) } Covariance { pos_0 0.0001; X-Covariance of initial position [m^2] pos_1 0.0001; Y-Covariance of initial position [m^2] pos_2 0.0001; Z-Covariance of initial position [m^2] vel_0 1.0; X-Covariance of initial velocity [m^2/s^2] vel_1 1.0; Y-Covariance of initial velocity [m^2/s^2] vel_2 1.0; Z-Covariance of initial velocity [m^2/s^2] acb_0 4e-4; X-Covariance of initial accelerometer bias [m^2/s^4] acb_1 4e-4; Y-Covariance of initial accelerometer bias [m^2/s^4] acb_2 4e-4; Z-Covariance of initial accelerometer bias [m^2/s^4] gyb_0 3e-4; X-Covariance of initial gyroscope bias [rad^2/s^2] gyb_1 3e-4; Y-Covariance of initial gyroscope bias [rad^2/s^2] gyb_2 3e-4; Z-Covariance of initial gyroscope bias [rad^2/s^2] vep 0.0001; Covariance of initial linear camera-IMU extrinsics, same for all entries [m^2] att_0 0.1; X-Covariance of initial attitude [rad^2] att_1 0.1; Y-Covariance of initial attitude [rad^2] att_2 0.1; Z-Covariance of initial attitude [rad^2] vea 0.01; Covariance of initial rotational camera-IMU extrinsics, same for all entries [rad^2] } } ImgUpdate { updateVecNormTermination 1e-4; maxNumIteration 20; doPatchWarping true; Should the patches be warped doFrameVisualisation true; Should the frames be visualized visualizePatches false; Should the patches be visualized useDirectMethod true; Should the EKF-innovation be based on direct intensity error (o.w. reprojection error) startLevel 2; Highest patch level which is being employed (must be smaller than the hardcoded template parameter) endLevel 1; Lowest patch level which is being employed nDetectionBuckets 100; Number of discretization buckets used during the candidates selection MahalanobisTh 9.21; Mahalanobis treshold for the update, 5.8858356 UpdateNoise { pix 2; Covariance used for the reprojection error, 1/focal_length is roughly 1 pixel std [rad] (~1/f ~ 1/400^2 = 1/160000) int 400; Covariance used for the photometric error [intensity^2] } initCovFeature_0 0.5; Covariance for the initial distance (Relative to initialization depth [m^2/m^2]) initCovFeature_1 1e-5; Covariance for the initial bearing vector, x-component [rad^2] initCovFeature_2 1e-5; Covariance for the initial bearing vector, y-component [rad^2] initDepth 0.5; Initial value for the initial distance parameter startDetectionTh 0.8; Threshold for detecting new features (min: 0, max: 1) scoreDetectionExponent 0.25; Exponent used for weighting the distance between candidates penaltyDistance 100; Maximal distance which gets penalized during bucketing [pix] zeroDistancePenalty 100; Penalty for zero distance (max: nDetectionBuckets) statLocalQualityRange 10; Number of frames for local quality evaluation statLocalVisibilityRange 100; Number of frames for local visibility evaluation statMinGlobalQualityRange 100; Minimum number of frames for obtaining maximal global quality trackingUpperBound 0.9; Threshold for local quality for min overall global quality trackingLowerBound 0.8; Threshold for local quality for max overall global quality minTrackedAndFreeFeatures 0.75; Minimum of amount of feature which are either tracked or free removalFactor 1.1; Factor for enforcing feature removal if not enough free minRelativeSTScore 0.75; Minimum relative ST-score for extracting new feature patch minAbsoluteSTScore 5.0; Minimum absolute ST-score for extracting new feature patch minTimeBetweenPatchUpdate 1.0; Minimum time between new multilevel patch extrection [s] fastDetectionThreshold 5; Fast corner detector treshold while adding new feature alignConvergencePixelRange 10; Assumed convergence range for image alignment (gets scaled with the level) [pixels] alignCoverageRatio 2; How many sigma of the uncertainty should be covered in the adaptive alignement alignMaxUniSample 1; Maximal number of alignment seeds on one side -> total number of sample = 2n+1. Carefull can get very costly if diverging! patchRejectionTh 50.0; If the average itensity error is larger than this the feauture is rejected [intensity], if smaller 0 the no check is performed alignmentHuberNormThreshold 10; Intensity error threshold for Huber norm (enabled if > 0) alignmentGaussianWeightingSigma -1; Width of Gaussian which is used for pixel error weighting (enabled if > 0) alignmentGradientExponent 0.0; Exponent used for gradient based weighting of residuals useIntensityOffsetForAlignment true; Should an intensity offset between the patches be considered useIntensitySqewForAlignment true; Should an intensity sqew between the patches be considered removeNegativeFeatureAfterUpdate true; Should feature with negative distance get removed maxUncertaintyToDepthRatioForDepthInitialization 0.3; If set to 0.0 the depth is initialized with the standard value provided above, otherwise ROVIO attempts to figure out a median depth in each frame useCrossCameraMeasurements true; Should cross measurements between frame be used. Might be turned of in calibration phase. doStereoInitialization true; Should a stereo match be used for feature initialization. noiseGainForOffCamera 10.0; Factor added on update noise if not main camera discriminativeSamplingDistance 0.02; Sampling distance for checking discriminativity of patch (if <= 0.0 no check is performed). discriminativeSamplingGain 1.1; Gain for threshold above which the samples must lie (if <= 1.0 the patchRejectionTh is used). MotionDetection { isEnabled 0; Is the motion detection enabled rateOfMovingFeaturesTh 0.5; Amount of feature with motion for overall motion detection pixelCoordinateMotionTh 1.0; Threshold for motion detection for patched [pixels] minFeatureCountForNoMotionDetection 5; Min feature count in frame for motion detection } ZeroVelocityUpdate { UpdateNoise { vel_0 0.01; X-Covariance of zero velocity update [m^2/s^2] vel_1 0.01; Y-Covariance of zero velocity update [m^2/s^2] vel_2 0.01; Z-Covariance of zero velocity update [m^2/s^2] } MahalanobisTh0 7.689997599999999; Mahalanobid distance for zero velocity updates minNoMotionTime 1.0; Min duration of no-motion isEnabled 0; Should zero velocity update be applied, only works if MotionDetection.isEnabled is true } } Prediction { PredictionNoise { pos_0 1e-4; X-covariance parameter of position prediction [m^2/s] pos_1 1e-4; Y-covariance parameter of position prediction [m^2/s] pos_2 1e-4; Z-covariance parameter of position prediction [m^2/s] vel_0 4e-6; X-covariance parameter of velocity prediction [m^2/s^3] vel_1 4e-6; Y-covariance parameter of velocity prediction [m^2/s^3] vel_2 4e-6; Z-covariance parameter of velocity prediction [m^2/s^3] acb_0 1e-8; X-covariance parameter of accelerometer bias prediction [m^2/s^5] acb_1 1e-8; Y-covariance parameter of accelerometer bias prediction [m^2/s^5] acb_2 1e-8; Z-covariance parameter of accelerometer bias prediction [m^2/s^5] gyb_0 3.8e-7; X-covariance parameter of gyroscope bias prediction [rad^2/s^3] gyb_1 3.8e-7; Y-covariance parameter of gyroscope bias prediction [rad^2/s^3] gyb_2 3.8e-7; Z-covariance parameter of gyroscope bias prediction [rad^2/s^3] vep 1e-8; Covariance parameter of linear extrinsics prediction [m^2/s] att_0 7.6e-7; X-Covariance parameter of attitude prediction [rad^2/s] att_1 7.6e-7; Y-Covariance parameter of attitude prediction [rad^2/s] att_2 7.6e-7; Z-Covariance parameter of attitude prediction [rad^2/s] vea 1e-8; Covariance parameter of rotational extrinsics prediction [rad^2/s] dep 0.0001; Covariance parameter of distance prediction [m^2/s] nor 0.00001; Covariance parameter of bearing vector prediction [rad^2/s] } MotionDetection { inertialMotionRorTh 0.1; Treshold on rotational rate for motion detection [rad/s] inertialMotionAccTh 0.5; Treshold on acceleration for motion detection [m/s^2] } } PoseUpdate { UpdateNoise { pos_0 0.01; X-Covariance of linear pose measurement update [m^2] pos_1 0.01; Y-Covariance of linear pose measurement update [m^2] pos_2 0.01; Z-Covariance of linear pose measurement update [m^2] att_0 0.01; X-Covariance of rotational pose measurement update [rad^2] att_1 0.01; Y-Covariance of rotational pose measurement update [rad^2] att_2 0.01; Z-Covariance of rotational pose measurement update [rad^2] } init_cov_IrIW 1; Covariance of initial pose between inertial frames, linear part [m^2] init_cov_qWI 1; Covariance of initial pose between inertial frames, rotational part [rad^2] init_cov_MrMV 1; Covariance of initial pose between inertial frames, linear part [m^2] init_cov_qVM 1; Covariance of initial pose between inertial frames, rotational part [rad^2] pre_cov_IrIW 1e-4; Covariance parameter of pose between inertial frames, linear part [m^2/s] pre_cov_qWI 1e-4; Covariance parameter of pose between inertial frames, rotational part [rad^2/s] pre_cov_MrMV 1e-4; Covariance parameter of pose between inertial frames, linear part [m^2/s] pre_cov_qVM 1e-4; Covariance parameter of pose between inertial frames, rotational part [rad^2/s] MahalanobisTh0 12.6511204; Mahalonobis distance treshold of pose measurement doVisualization false; Should the measured poses be vizualized enablePosition true; Should the linear part be used during the update enableAttitude true; Should the rotation part be used during the update (e.g. set to fals eif feeding GPS-measurement) noFeedbackToRovio true; By default the pose update is only used for aligning coordinate frame. Set to false if ROVIO should benefit frome the posed measurements. doInertialAlignmentAtStart true; Should the transformation between I and W be explicitly computed and set with the first pose measurement. timeOffset 0.0; Time offset added to the pose measurement timestamps useOdometryCov false; Should the UpdateNoise position covariance be scaled using the covariance in the Odometry message qVM_x 0; X-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) qVM_y 0; Y-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) qVM_z 0; Z-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) qVM_w 1; W-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) MrMV_x 0; X-entry of vector representing IMU to reference body coordinate frame of pose measurement MrMV_y 0; Y-entry of vector representing IMU to reference body coordinate frame of pose measurement MrMV_z 0; Z-entry of vector representing IMU to reference body coordinate frame of pose measurement qWI_x 0; X-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) qWI_y 0; Y-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) qWI_z 0; Z-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) qWI_w 1; W-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) IrIW_x 0; X-entry of vector representing World to reference inertial coordinate frame of pose measurement IrIW_y 0; Y-entry of vector representing World to reference inertial coordinate frame of pose measurement IrIW_z 0; Z-entry of vector representing World to reference inertial coordinate frame of pose measurement } VelocityUpdate { UpdateNoise { vel_0 0.0001 vel_1 0.0001 vel_2 0.0001 } MahalanobisTh0 7.689997599999999 qAM_x 0 qAM_y 0 qAM_z 0 qAM_w 1 }
This is the following error that I'm getting:
cv_bridge exception: [rgb8] is a color format but [8UC1] is not so they must have the same OpenCV type, CV_8UC3, CV16UC1 ....I've made the following changes in the files:src/launch/rovio_node.launch ` <?xml version="1.0" encoding="UTF-8"?>
`
src/cfg/rovio_camr.yaml
image_width: 640 image_height: 480 camera_name: camr camera_matrix: rows: 3 cols: 3 data: [595.769226118, 0.0, 315.630153866, 0.0, 601.100099736, 249.900958294, 0.0, 0.0, 1.0] distortion_model: equidistant distortion_coefficients: rows: 1 cols: 4 data: [0.360048202645, 1.38084511511, -8.16744585152, 13.4516399414]src/cfg/rovio.info
; You can partially override parameter set in this file by creating your own subset of parameter in a separate info-file and include it with: ; #include "/home/user/workspace/rovio/cfg/rovio_custom.info" Common { doVECalibration true; Should the camera-IMU extrinsics be calibrated online depthType 1; Type of depth parametrization (0: normal, 1: inverse depth, 2: log, 3: hyperbolic) verbose false; Is the verbose active } Camera0 { CalibrationFile ; Camera-Calibration file for intrinsics qCM_x 0.00666398307551; X-entry of IMU to Camera quaterion (Hamilton) qCM_y -0.0079168224269; Y-entry of IMU to Camera quaterion (Hamilton) qCM_z -0.701985972528; Z-entry of IMU to Camera quaterion (Hamilton) qCM_w 0.712115587266; W-entry of IMU to Camera quaterion (Hamilton) MrMC_x -0.0111674199187; X-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_y -0.0574640920022; Y-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_z 0.0207586947896; Z-entry of IMU to Camera vector (expressed in IMU CF) [m] } Camera1 { CalibrationFile ; Camera-Calibration file for intrinsics qCM_x 0.00151329637706; X-entry of IMU to Camera quaterion (Hamilton) qCM_y -0.0123329249764; Y-entry of IMU to Camera quaterion (Hamilton) qCM_z -0.702657352863; Z-entry of IMU to Camera quaterion (Hamilton) qCM_w 0.711419885414; W-entry of IMU to Camera quaterion (Hamilton) MrMC_x -0.0091929160801; X-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_y 0.0540646643676; Y-entry of IMU to Camera vector (expressed in IMU CF) [m] MrMC_z 0.0190387660614; Z-entry of IMU to Camera vector (expressed in IMU CF) [m] } Init { State { pos_0 0; X-entry of initial position (world to IMU in world) [m] pos_1 0; Y-entry of initial position (world to IMU in world) [m] pos_2 0; Z-entry of initial position (world to IMU in world) [m] vel_0 0; X-entry of initial velocity (robocentric, IMU) [m/s] vel_1 0; Y-entry of initial velocity (robocentric, IMU) [m/s] vel_2 0; Z-entry of initial velocity (robocentric, IMU) [m/s] acb_0 0; X-entry of accelerometer bias [m/s^2] acb_1 0; Y-entry of accelerometer bias [m/s^2] acb_2 0; Z-entry of accelerometer bias [m/s^2] gyb_0 0; X-entry of gyroscope bias [rad/s] gyb_1 0; Y-entry of gyroscope bias [rad/s] gyb_2 0; Z-entry of gyroscope bias [rad/s] att_x 0; X-entry of initial attitude (IMU to world, Hamilton) att_y 0; Y-entry of initial attitude (IMU to world, Hamilton) att_z 0; Z-entry of initial attitude (IMU to world, Hamilton) att_w 1; W-entry of initial attitude (IMU to world, Hamilton) } Covariance { pos_0 0.0001; X-Covariance of initial position [m^2] pos_1 0.0001; Y-Covariance of initial position [m^2] pos_2 0.0001; Z-Covariance of initial position [m^2] vel_0 1.0; X-Covariance of initial velocity [m^2/s^2] vel_1 1.0; Y-Covariance of initial velocity [m^2/s^2] vel_2 1.0; Z-Covariance of initial velocity [m^2/s^2] acb_0 4e-4; X-Covariance of initial accelerometer bias [m^2/s^4] acb_1 4e-4; Y-Covariance of initial accelerometer bias [m^2/s^4] acb_2 4e-4; Z-Covariance of initial accelerometer bias [m^2/s^4] gyb_0 3e-4; X-Covariance of initial gyroscope bias [rad^2/s^2] gyb_1 3e-4; Y-Covariance of initial gyroscope bias [rad^2/s^2] gyb_2 3e-4; Z-Covariance of initial gyroscope bias [rad^2/s^2] vep 0.0001; Covariance of initial linear camera-IMU extrinsics, same for all entries [m^2] att_0 0.1; X-Covariance of initial attitude [rad^2] att_1 0.1; Y-Covariance of initial attitude [rad^2] att_2 0.1; Z-Covariance of initial attitude [rad^2] vea 0.01; Covariance of initial rotational camera-IMU extrinsics, same for all entries [rad^2] } } ImgUpdate { updateVecNormTermination 1e-4; maxNumIteration 20; doPatchWarping true; Should the patches be warped doFrameVisualisation true; Should the frames be visualized visualizePatches false; Should the patches be visualized useDirectMethod true; Should the EKF-innovation be based on direct intensity error (o.w. reprojection error) startLevel 2; Highest patch level which is being employed (must be smaller than the hardcoded template parameter) endLevel 1; Lowest patch level which is being employed nDetectionBuckets 100; Number of discretization buckets used during the candidates selection MahalanobisTh 9.21; Mahalanobis treshold for the update, 5.8858356 UpdateNoise { pix 2; Covariance used for the reprojection error, 1/focal_length is roughly 1 pixel std [rad] (~1/f ~ 1/400^2 = 1/160000) int 400; Covariance used for the photometric error [intensity^2] } initCovFeature_0 0.5; Covariance for the initial distance (Relative to initialization depth [m^2/m^2]) initCovFeature_1 1e-5; Covariance for the initial bearing vector, x-component [rad^2] initCovFeature_2 1e-5; Covariance for the initial bearing vector, y-component [rad^2] initDepth 0.5; Initial value for the initial distance parameter startDetectionTh 0.8; Threshold for detecting new features (min: 0, max: 1) scoreDetectionExponent 0.25; Exponent used for weighting the distance between candidates penaltyDistance 100; Maximal distance which gets penalized during bucketing [pix] zeroDistancePenalty 100; Penalty for zero distance (max: nDetectionBuckets) statLocalQualityRange 10; Number of frames for local quality evaluation statLocalVisibilityRange 100; Number of frames for local visibility evaluation statMinGlobalQualityRange 100; Minimum number of frames for obtaining maximal global quality trackingUpperBound 0.9; Threshold for local quality for min overall global quality trackingLowerBound 0.8; Threshold for local quality for max overall global quality minTrackedAndFreeFeatures 0.75; Minimum of amount of feature which are either tracked or free removalFactor 1.1; Factor for enforcing feature removal if not enough free minRelativeSTScore 0.75; Minimum relative ST-score for extracting new feature patch minAbsoluteSTScore 5.0; Minimum absolute ST-score for extracting new feature patch minTimeBetweenPatchUpdate 1.0; Minimum time between new multilevel patch extrection [s] fastDetectionThreshold 5; Fast corner detector treshold while adding new feature alignConvergencePixelRange 10; Assumed convergence range for image alignment (gets scaled with the level) [pixels] alignCoverageRatio 2; How many sigma of the uncertainty should be covered in the adaptive alignement alignMaxUniSample 1; Maximal number of alignment seeds on one side -> total number of sample = 2n+1. Carefull can get very costly if diverging! patchRejectionTh 50.0; If the average itensity error is larger than this the feauture is rejected [intensity], if smaller 0 the no check is performed alignmentHuberNormThreshold 10; Intensity error threshold for Huber norm (enabled if > 0) alignmentGaussianWeightingSigma -1; Width of Gaussian which is used for pixel error weighting (enabled if > 0) alignmentGradientExponent 0.0; Exponent used for gradient based weighting of residuals useIntensityOffsetForAlignment true; Should an intensity offset between the patches be considered useIntensitySqewForAlignment true; Should an intensity sqew between the patches be considered removeNegativeFeatureAfterUpdate true; Should feature with negative distance get removed maxUncertaintyToDepthRatioForDepthInitialization 0.3; If set to 0.0 the depth is initialized with the standard value provided above, otherwise ROVIO attempts to figure out a median depth in each frame useCrossCameraMeasurements true; Should cross measurements between frame be used. Might be turned of in calibration phase. doStereoInitialization true; Should a stereo match be used for feature initialization. noiseGainForOffCamera 10.0; Factor added on update noise if not main camera discriminativeSamplingDistance 0.02; Sampling distance for checking discriminativity of patch (if <= 0.0 no check is performed). discriminativeSamplingGain 1.1; Gain for threshold above which the samples must lie (if <= 1.0 the patchRejectionTh is used). MotionDetection { isEnabled 0; Is the motion detection enabled rateOfMovingFeaturesTh 0.5; Amount of feature with motion for overall motion detection pixelCoordinateMotionTh 1.0; Threshold for motion detection for patched [pixels] minFeatureCountForNoMotionDetection 5; Min feature count in frame for motion detection } ZeroVelocityUpdate { UpdateNoise { vel_0 0.01; X-Covariance of zero velocity update [m^2/s^2] vel_1 0.01; Y-Covariance of zero velocity update [m^2/s^2] vel_2 0.01; Z-Covariance of zero velocity update [m^2/s^2] } MahalanobisTh0 7.689997599999999; Mahalanobid distance for zero velocity updates minNoMotionTime 1.0; Min duration of no-motion isEnabled 0; Should zero velocity update be applied, only works if MotionDetection.isEnabled is true } } Prediction { PredictionNoise { pos_0 1e-4; X-covariance parameter of position prediction [m^2/s] pos_1 1e-4; Y-covariance parameter of position prediction [m^2/s] pos_2 1e-4; Z-covariance parameter of position prediction [m^2/s] vel_0 4e-6; X-covariance parameter of velocity prediction [m^2/s^3] vel_1 4e-6; Y-covariance parameter of velocity prediction [m^2/s^3] vel_2 4e-6; Z-covariance parameter of velocity prediction [m^2/s^3] acb_0 1e-8; X-covariance parameter of accelerometer bias prediction [m^2/s^5] acb_1 1e-8; Y-covariance parameter of accelerometer bias prediction [m^2/s^5] acb_2 1e-8; Z-covariance parameter of accelerometer bias prediction [m^2/s^5] gyb_0 3.8e-7; X-covariance parameter of gyroscope bias prediction [rad^2/s^3] gyb_1 3.8e-7; Y-covariance parameter of gyroscope bias prediction [rad^2/s^3] gyb_2 3.8e-7; Z-covariance parameter of gyroscope bias prediction [rad^2/s^3] vep 1e-8; Covariance parameter of linear extrinsics prediction [m^2/s] att_0 7.6e-7; X-Covariance parameter of attitude prediction [rad^2/s] att_1 7.6e-7; Y-Covariance parameter of attitude prediction [rad^2/s] att_2 7.6e-7; Z-Covariance parameter of attitude prediction [rad^2/s] vea 1e-8; Covariance parameter of rotational extrinsics prediction [rad^2/s] dep 0.0001; Covariance parameter of distance prediction [m^2/s] nor 0.00001; Covariance parameter of bearing vector prediction [rad^2/s] } MotionDetection { inertialMotionRorTh 0.1; Treshold on rotational rate for motion detection [rad/s] inertialMotionAccTh 0.5; Treshold on acceleration for motion detection [m/s^2] } } PoseUpdate { UpdateNoise { pos_0 0.01; X-Covariance of linear pose measurement update [m^2] pos_1 0.01; Y-Covariance of linear pose measurement update [m^2] pos_2 0.01; Z-Covariance of linear pose measurement update [m^2] att_0 0.01; X-Covariance of rotational pose measurement update [rad^2] att_1 0.01; Y-Covariance of rotational pose measurement update [rad^2] att_2 0.01; Z-Covariance of rotational pose measurement update [rad^2] } init_cov_IrIW 1; Covariance of initial pose between inertial frames, linear part [m^2] init_cov_qWI 1; Covariance of initial pose between inertial frames, rotational part [rad^2] init_cov_MrMV 1; Covariance of initial pose between inertial frames, linear part [m^2] init_cov_qVM 1; Covariance of initial pose between inertial frames, rotational part [rad^2] pre_cov_IrIW 1e-4; Covariance parameter of pose between inertial frames, linear part [m^2/s] pre_cov_qWI 1e-4; Covariance parameter of pose between inertial frames, rotational part [rad^2/s] pre_cov_MrMV 1e-4; Covariance parameter of pose between inertial frames, linear part [m^2/s] pre_cov_qVM 1e-4; Covariance parameter of pose between inertial frames, rotational part [rad^2/s] MahalanobisTh0 12.6511204; Mahalonobis distance treshold of pose measurement doVisualization false; Should the measured poses be vizualized enablePosition true; Should the linear part be used during the update enableAttitude true; Should the rotation part be used during the update (e.g. set to fals eif feeding GPS-measurement) noFeedbackToRovio true; By default the pose update is only used for aligning coordinate frame. Set to false if ROVIO should benefit frome the posed measurements. doInertialAlignmentAtStart true; Should the transformation between I and W be explicitly computed and set with the first pose measurement. timeOffset 0.0; Time offset added to the pose measurement timestamps useOdometryCov false; Should the UpdateNoise position covariance be scaled using the covariance in the Odometry message qVM_x 0; X-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) qVM_y 0; Y-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) qVM_z 0; Z-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) qVM_w 1; W-entry of quaterion representing IMU to reference body coordinate frame of pose measurement (Hamilton) MrMV_x 0; X-entry of vector representing IMU to reference body coordinate frame of pose measurement MrMV_y 0; Y-entry of vector representing IMU to reference body coordinate frame of pose measurement MrMV_z 0; Z-entry of vector representing IMU to reference body coordinate frame of pose measurement qWI_x 0; X-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) qWI_y 0; Y-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) qWI_z 0; Z-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) qWI_w 1; W-entry of quaterion representing World to reference inertial coordinate frame of pose measurement (Hamilton) IrIW_x 0; X-entry of vector representing World to reference inertial coordinate frame of pose measurement IrIW_y 0; Y-entry of vector representing World to reference inertial coordinate frame of pose measurement IrIW_z 0; Z-entry of vector representing World to reference inertial coordinate frame of pose measurement } VelocityUpdate { UpdateNoise { vel_0 0.0001 vel_1 0.0001 vel_2 0.0001 } MahalanobisTh0 7.689997599999999 qAM_x 0 qAM_y 0 qAM_z 0 qAM_w 1 }