ODyN

Online Dynamic Network solver

Davide A. Cucci

davide.cucci@gmail.com

With the collaboration and support of

Jan Skaloud

Geodetic Engineering Laboratory (TOPO)

Ecole Polytechnique Fédérale de Lausanne, Switzerland

jan.skaloud@epfl.ch

| Documentation | Report an issue |

| dn rev: 59eb579 | ROAMFREE rev: 3abac19 | built on 07-04-2024 15:27:38 |

Inputs

Measurements

A single .zip file containing all input files must be provided below.

Upload file [.zip]

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Files interpred in Global (WGS84) coordinate system by default. If data is expressed in 'Local' frame, please change corresponding setting under 'Processing options'

System configuration (optional)

A saved configuration can be restored providing a file below.

Upload file [.RData]

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Processing options

Coordinate System (In/Out)

Depending on input data, select if either local or global frame should be used for fusion.

Fusion Frame

Warning: only use 'Local' when fusing low quality IMU

IMU pre-integration

Number of IMU epochs to pre-integrate

Pre Integration Factor 2250010258111417202325

Trajectory initialization

Sensors

Lever arm (body -> Antenna, i.e., Antenna^b)

X [m]

Y [m]

Z [m]

Estimate lever arm

Precision (1-sigma)

Robustify GNSS measurements

Lever arm (body -> IMU, i.e., IMU^b)

X [m]

Y [m]

Z [m]

Estimate lever arm

Boresight (R^b_IMU) [unit quaternion]

Estimate boresight

Accelerometer

How many Gauss-Markov processes?

White Noise

Std [ug/sqrt(Hz)]

Gyroscope

How many Gauss-Markov processes?

White Noise

Std [deg/h/sqrt(Hz)]

Lever arm (body -> Camera, i.e., Camera^b)

X [m]

Y [m]

Z [m]

Estimate lever arm

Boresight (R^b_Camera) [unit quaternion]

Estimate boresight

Intrinsic camera calibration

Image width [px]

Image height [px]

f [px]

cx [px]

cy [px]

Estimate intrinsic camera calibration

Lens distortion

Radial: K1 []

K2 []

K3 []

K4 []

Tangential: P1 []

P2 []

Skew: B1 [px]

B2 [px]

Estimate lens distortions

Image measurements precision (1-sigma)

Tie Points std [px]

Ground Control Points (selected) / Checkpoints

Selectd rows in the table below will be used as GCPs.

Image precision (1-sigma)

GCPs std [px]

Precision on ground (1-sigma)

E [m]

N [m]

U [m]

Lever arm (body -> LiDAR, i.e., LiDAR^b)

X [m]

Y [m]

Z [m]

Estimate lever arm

Boresight (R^b_LiDAR) [unit quaternion]

Estimate boresight

Precision

P2p correspondences std [m]

Robustify P2P measurements

Processing

Input status

Time selection

Start [s]

End [s]

Preview

Run the processing

Results

Processing status

[Advanced] Show DN output

DN output

Save

Download system configuration

Online Dynamic Network solver

Davide A. Cucci

davide.cucci@gmail.com

With the collaboration and support of

Jan Skaloud

Geodetic Engineering Laboratory (TOPO)

Ecole Polytechnique Fédérale de Lausanne, Switzerland

jan.skaloud@epfl.ch

| dn rev: 59eb579 | ROAMFREE rev: 3abac19 | built on 07-04-2024 15:27:38 |

Inputs

Measurements

A single .zip file containing all input files must be provided below.

System configuration (optional)

A saved configuration can be restored providing a file below.

Processing options

Coordinate System (In/Out)

Depending on input data, select if either local or global frame should be used for fusion.

IMU pre-integration

Number of IMU epochs to pre-integrate

Trajectory initialization

If an initial guess for the trajectory is not provided, the orientation of the body frame with respect to the vehicle should be provided.

Initial guess provided, automatic initialization disabled.

Sensors

Lever arm (body -> Antenna, i.e., Antennab)

Lever arm uncertainty

Precision (1-sigma)

Precision provided in the input file

Robustify GNSS measurements

Usefull for terrestrial & indoor applications with drifting position estimation (e.g. visual odometry)

Processing

Input status

Time selection

Preview

Run the processing

Results

Processing status

DN output

Save

Lever arm (body -> Antenna, i.e., Antenna^b)