
Package Summary
Tags  No category tags. 
Version  1.2.0 
License  Apache License 2.0 
Build type  AMENT_CMAKE 
Use  RECOMMENDED 
Repository Summary
Checkout URI  https://github.com/autowarefoundation/autoware_msgs.git 
VCS Type  git 
VCS Version  main 
Last Updated  20241031 
Dev Status  DEVELOPED 
CI status  No Continuous Integration 
Released  RELEASED 
Tags  No category tags. 
Contributing 
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) 
Package Description
Additional Links
Maintainers
 Yutaka Kondo
 M. Fatih Cırıt
Authors
autoware_sensing_msgs
GNSS/INS sensor messages
Possible Data Types:
 Position
 Orientation
 Twist (Velocity)
 linear
 angular
 Accel
 linear
 angular
Position
For this information, you can use the NavSatFix message.
If the sensor provides MSL(Mean Sea Level) for altitude, you can use it for the altitude field.

sensor_msgs/NavSatFix
following fields are used:
std_msgs/Header
header 
float64
latitude 
float64
longitude 
float64
altitude 
float64[9]
position_covariance

For detailed info about the east, north, up, see the Coordinate Axes Conventions.
Orientation
GnssInsOrientationStamped.msg
This message contains the GNSSINS orientation information.
The orientation is represented by a quaternion.
If the sensor provides roll, pitch, yaw; you should convert it to quaternion.
For detailed info about the roll, pitch, yaw and rotation axes see the Coordinate Axes Conventions.
Velocity
For this information, you can use the TwistWithCovarianceStamped message.
Its structure is as follows:

geometry_msgs/TwistWithCovarianceStamped
following fields are used:
std_msgs/Header
header 
geometry_msgs/TwistWithCovariance
twist
geometry_msgs/Twist
twist
geometry_msgs/Vector3
linear 
geometry_msgs/Vector3
angular


float64[36]
covariance


 The linear field contains the linear velocities in the x, y, z axes.
 The angular field contains the angular velocities in the x, y, z axes.
 The covariance matrix parameters are linear and angular velocities in order.
For detailed info about the covariance matrix RMSE? Variances? Covariance Matrix?.
Acceleration
For this information, you can use the AccelWithCovarianceStamped message.
Its structure is as follows:

geometry_msgs/AccelWithCovarianceStamped
following fields are used:
std_msgs/Header
header 
geometry_msgs/AccelWithCovariance
accel
geometry_msgs/Accel
accel
geometry_msgs/Vector3
linear 
geometry_msgs/Vector3
angular


float64[36]
covariance


 The linear field contains the linear accelerations in the x, y, z axes.
 The angular field contains the angular accelerations in the x, y, z axes.
 The covariance matrix parameters are linear and angular accelerations in order.
For detailed info about the covariance matrix RMSE? Variances? Covariance Matrix?.
Design
Coordinate Frames
Frames used in Autoware are defined as follows:
flowchart LR
earth > Map[map] > base_link
base_link > gnss_ins
base_link > sensor_a
base_link > sensor_b
In Autoware, the earth
frame is mostly omitted, only used in the GnssInsPositionStamped
message.
The map
frame is used as the stationary reference frame.
The map
frame’s axes point to the East, North, Up directions as explained in Coordinate Axes Conventions.
The base_link
is the center of the rear axle of the vehicle.
Map[map] > base_link
is the main transformation that is attempted to be estimated by various localization modules. This transformation is output by the EKF(Extended Kalman Filter) localization module.
Other sensors’ frames are defined with respect to the base_link
frame in the vehicle.
Estimating the base_link
frame by using the other sensors
Generally we don’t have the localization sensors physically at the base_link
frame. So various sensors localize with respect to their own frames, let’s call it sensor
frame.
We introduce a new frame naming convention: x_by_y
:
x: estimated frame name
y: localization method/source
We cannot directly get the sensor
frame. Because we would need the EKF module to estimate the base_link
frame first.
Without the EKF module the best we can do is to estimate Map[map] > sensor_by_sensor > base_link_by_sensor
using this sensor.
Example by the GNSS/INS sensor
For the integrated GNSS/INS we use the following frames:
flowchart LR
earth > Map[map] > gnss_ins_by_gnss_ins > base_link_by_gnss_ins
The gnss_ins_by_gnss_ins
frame is obtained by the coordinates from GNSS/INS sensor. The coordinates are converted to map
frame using the gnss_poser
node.
Finally gnss_ins_by_gnss_ins
frame represents the position of the gnss_ins
estimated by the gnss_ins
sensor in the map
.
Then by using the static transformation between gnss_ins
and the base_link
frame, we can obtain the base_link_by_gnss_ins
frame. Which represents the base_link
estimated by the gnss_ins
sensor.
References:
Coordinate Axes Conventions
We are using East, North, Up (ENU) coordinate axes convention by default throughout the stack.
X+: East
Y+: North
Z+: Up
The position, orientation, velocity, acceleration are all defined in the same axis convention.
Position by the GNSS/INS sensor is expected to be in earth
frame.
Orientation, velocity, acceleration by the GNSS/INS sensor are expected to be in the sensor frame. Axes parallel to the map
frame.
If roll, pitch, yaw is provided, they correspond to rotation around X, Y, Z axes respectively.
Rotation around:
X+: roll
Y+: pitch
Z+: yaw
References:
RMSE? Variances? Covariance Matrix?
Definitions
RMSE: Root Mean Square Error is a measure of the differences between values predicted by a model or an estimator and the values observed.
Variance: Squared deviation of a random variable from its sample mean.
Covariance: A measure of the joint variability of two random variables.
Covariance Matrix: A square matrix giving the covariance between each pair of elements of a given random vector
Simplified usage in Autoware
RMSE² = Variance
A covariance matrix is of n
random variables is an n×n
matrix.
Covariance with itself is the variance of the random variable.
The diagonal elements of the covariance matrix are the variances of the random variables.
In Autoware, only these variance values are used, mostly in the RMSE form. The rest of the covariance matrix is not used, can be left 0.0
.
Example for TwistWithCovariance
This message contains the linear and angular velocities and the covariance matrix.
Let’s call RMSE values for these calculations as σ_x, σ_y, σ_z, σ_r, σ_p, σ_y
.
The covariance matrix can be constructed as follows:
σ_x  0  0  0  0  0 
0  σ_y  0  0  0  0 
0  0  σ_z  0  0  0 
0  0  0  σ_r  0  0 
0  0  0  0  σ_p  0 
0  0  0  0  0  σ_y 
In the message file, it is a float64[36]
array. We fill the indices at i*7, i:[0,6]
, making up 0,7,14,21,28,35
th indices of this array.
References:
 https://en.wikipedia.org/wiki/Rootmeansquare_deviation
 https://en.wikipedia.org/wiki/Variance#Biased_sample_variance
 https://en.wikipedia.org/wiki/Covariance#Covariance_with_itself
 https://en.wikipedia.org/wiki/Covariance_matrix
Q/A
 Why is position and orientation not combined as a PoseWithCovarianceStamped message?
 Modern GNSS/INS sensors provide both of these together but more affordable gnss only sensors might provide only position information.
 We separated them to allow if the INS sensor is separate, the orientation information can be extracted from there with aid of a magnetometer.
Changelog for package autoware_sensing_msgs
1.2.0 (20241001)
1.1.0 (20240510)
Wiki Tutorials
Package Dependencies
Deps  Name 

ament_cmake_auto  
rosidl_default_generators  
rosidl_default_runtime  
ament_lint_auto  
ament_lint_common  
geometry_msgs  
std_msgs 
System Dependencies
Dependant Packages
Launch files
Services
Plugins
Recent questions tagged autoware_sensing_msgs at Robotics Stack Exchange

Package Summary
Tags  No category tags. 
Version  1.2.0 
License  Apache License 2.0 
Build type  AMENT_CMAKE 
Use  RECOMMENDED 
Repository Summary
Checkout URI  https://github.com/autowarefoundation/autoware_msgs.git 
VCS Type  git 
VCS Version  main 
Last Updated  20241031 
Dev Status  DEVELOPED 
CI status  No Continuous Integration 
Released  RELEASED 
Tags  No category tags. 
Contributing 
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) 
Package Description
Additional Links
Maintainers
 Yutaka Kondo
 M. Fatih Cırıt
Authors
autoware_sensing_msgs
GNSS/INS sensor messages
Possible Data Types:
 Position
 Orientation
 Twist (Velocity)
 linear
 angular
 Accel
 linear
 angular
Position
For this information, you can use the NavSatFix message.
If the sensor provides MSL(Mean Sea Level) for altitude, you can use it for the altitude field.

sensor_msgs/NavSatFix
following fields are used:
std_msgs/Header
header 
float64
latitude 
float64
longitude 
float64
altitude 
float64[9]
position_covariance

For detailed info about the east, north, up, see the Coordinate Axes Conventions.
Orientation
GnssInsOrientationStamped.msg
This message contains the GNSSINS orientation information.
The orientation is represented by a quaternion.
If the sensor provides roll, pitch, yaw; you should convert it to quaternion.
For detailed info about the roll, pitch, yaw and rotation axes see the Coordinate Axes Conventions.
Velocity
For this information, you can use the TwistWithCovarianceStamped message.
Its structure is as follows:

geometry_msgs/TwistWithCovarianceStamped
following fields are used:
std_msgs/Header
header 
geometry_msgs/TwistWithCovariance
twist
geometry_msgs/Twist
twist
geometry_msgs/Vector3
linear 
geometry_msgs/Vector3
angular


float64[36]
covariance


 The linear field contains the linear velocities in the x, y, z axes.
 The angular field contains the angular velocities in the x, y, z axes.
 The covariance matrix parameters are linear and angular velocities in order.
For detailed info about the covariance matrix RMSE? Variances? Covariance Matrix?.
Acceleration
For this information, you can use the AccelWithCovarianceStamped message.
Its structure is as follows:

geometry_msgs/AccelWithCovarianceStamped
following fields are used:
std_msgs/Header
header 
geometry_msgs/AccelWithCovariance
accel
geometry_msgs/Accel
accel
geometry_msgs/Vector3
linear 
geometry_msgs/Vector3
angular


float64[36]
covariance


 The linear field contains the linear accelerations in the x, y, z axes.
 The angular field contains the angular accelerations in the x, y, z axes.
 The covariance matrix parameters are linear and angular accelerations in order.
For detailed info about the covariance matrix RMSE? Variances? Covariance Matrix?.
Design
Coordinate Frames
Frames used in Autoware are defined as follows:
flowchart LR
earth > Map[map] > base_link
base_link > gnss_ins
base_link > sensor_a
base_link > sensor_b
In Autoware, the earth
frame is mostly omitted, only used in the GnssInsPositionStamped
message.
The map
frame is used as the stationary reference frame.
The map
frame’s axes point to the East, North, Up directions as explained in Coordinate Axes Conventions.
The base_link
is the center of the rear axle of the vehicle.
Map[map] > base_link
is the main transformation that is attempted to be estimated by various localization modules. This transformation is output by the EKF(Extended Kalman Filter) localization module.
Other sensors’ frames are defined with respect to the base_link
frame in the vehicle.
Estimating the base_link
frame by using the other sensors
Generally we don’t have the localization sensors physically at the base_link
frame. So various sensors localize with respect to their own frames, let’s call it sensor
frame.
We introduce a new frame naming convention: x_by_y
:
x: estimated frame name
y: localization method/source
We cannot directly get the sensor
frame. Because we would need the EKF module to estimate the base_link
frame first.
Without the EKF module the best we can do is to estimate Map[map] > sensor_by_sensor > base_link_by_sensor
using this sensor.
Example by the GNSS/INS sensor
For the integrated GNSS/INS we use the following frames:
flowchart LR
earth > Map[map] > gnss_ins_by_gnss_ins > base_link_by_gnss_ins
The gnss_ins_by_gnss_ins
frame is obtained by the coordinates from GNSS/INS sensor. The coordinates are converted to map
frame using the gnss_poser
node.
Finally gnss_ins_by_gnss_ins
frame represents the position of the gnss_ins
estimated by the gnss_ins
sensor in the map
.
Then by using the static transformation between gnss_ins
and the base_link
frame, we can obtain the base_link_by_gnss_ins
frame. Which represents the base_link
estimated by the gnss_ins
sensor.
References:
Coordinate Axes Conventions
We are using East, North, Up (ENU) coordinate axes convention by default throughout the stack.
X+: East
Y+: North
Z+: Up
The position, orientation, velocity, acceleration are all defined in the same axis convention.
Position by the GNSS/INS sensor is expected to be in earth
frame.
Orientation, velocity, acceleration by the GNSS/INS sensor are expected to be in the sensor frame. Axes parallel to the map
frame.
If roll, pitch, yaw is provided, they correspond to rotation around X, Y, Z axes respectively.
Rotation around:
X+: roll
Y+: pitch
Z+: yaw
References:
RMSE? Variances? Covariance Matrix?
Definitions
RMSE: Root Mean Square Error is a measure of the differences between values predicted by a model or an estimator and the values observed.
Variance: Squared deviation of a random variable from its sample mean.
Covariance: A measure of the joint variability of two random variables.
Covariance Matrix: A square matrix giving the covariance between each pair of elements of a given random vector
Simplified usage in Autoware
RMSE² = Variance
A covariance matrix is of n
random variables is an n×n
matrix.
Covariance with itself is the variance of the random variable.
The diagonal elements of the covariance matrix are the variances of the random variables.
In Autoware, only these variance values are used, mostly in the RMSE form. The rest of the covariance matrix is not used, can be left 0.0
.
Example for TwistWithCovariance
This message contains the linear and angular velocities and the covariance matrix.
Let’s call RMSE values for these calculations as σ_x, σ_y, σ_z, σ_r, σ_p, σ_y
.
The covariance matrix can be constructed as follows:
σ_x  0  0  0  0  0 
0  σ_y  0  0  0  0 
0  0  σ_z  0  0  0 
0  0  0  σ_r  0  0 
0  0  0  0  σ_p  0 
0  0  0  0  0  σ_y 
In the message file, it is a float64[36]
array. We fill the indices at i*7, i:[0,6]
, making up 0,7,14,21,28,35
th indices of this array.
References:
 https://en.wikipedia.org/wiki/Rootmeansquare_deviation
 https://en.wikipedia.org/wiki/Variance#Biased_sample_variance
 https://en.wikipedia.org/wiki/Covariance#Covariance_with_itself
 https://en.wikipedia.org/wiki/Covariance_matrix
Q/A
 Why is position and orientation not combined as a PoseWithCovarianceStamped message?
 Modern GNSS/INS sensors provide both of these together but more affordable gnss only sensors might provide only position information.
 We separated them to allow if the INS sensor is separate, the orientation information can be extracted from there with aid of a magnetometer.
Changelog for package autoware_sensing_msgs
1.2.0 (20241001)
1.1.0 (20240510)
Wiki Tutorials
Package Dependencies
Deps  Name 

ament_cmake_auto  
rosidl_default_generators  
rosidl_default_runtime  
ament_lint_auto  
ament_lint_common  
geometry_msgs  
std_msgs 
System Dependencies
Dependant Packages
Launch files
Services
Plugins
Recent questions tagged autoware_sensing_msgs at Robotics Stack Exchange

Package Summary
Tags  No category tags. 
Version  1.2.0 
License  Apache License 2.0 
Build type  AMENT_CMAKE 
Use  RECOMMENDED 
Repository Summary
Checkout URI  https://github.com/autowarefoundation/autoware_msgs.git 
VCS Type  git 
VCS Version  main 
Last Updated  20241031 
Dev Status  DEVELOPED 
CI status  No Continuous Integration 
Released  RELEASED 
Tags  No category tags. 
Contributing 
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) 
Package Description
Additional Links
Maintainers
 Yutaka Kondo
 M. Fatih Cırıt
Authors
autoware_sensing_msgs
GNSS/INS sensor messages
Possible Data Types:
 Position
 Orientation
 Twist (Velocity)
 linear
 angular
 Accel
 linear
 angular
Position
For this information, you can use the NavSatFix message.
If the sensor provides MSL(Mean Sea Level) for altitude, you can use it for the altitude field.

sensor_msgs/NavSatFix
following fields are used:
std_msgs/Header
header 
float64
latitude 
float64
longitude 
float64
altitude 
float64[9]
position_covariance

For detailed info about the east, north, up, see the Coordinate Axes Conventions.
Orientation
GnssInsOrientationStamped.msg
This message contains the GNSSINS orientation information.
The orientation is represented by a quaternion.
If the sensor provides roll, pitch, yaw; you should convert it to quaternion.
For detailed info about the roll, pitch, yaw and rotation axes see the Coordinate Axes Conventions.
Velocity
For this information, you can use the TwistWithCovarianceStamped message.
Its structure is as follows:

geometry_msgs/TwistWithCovarianceStamped
following fields are used:
std_msgs/Header
header 
geometry_msgs/TwistWithCovariance
twist
geometry_msgs/Twist
twist
geometry_msgs/Vector3
linear 
geometry_msgs/Vector3
angular


float64[36]
covariance


 The linear field contains the linear velocities in the x, y, z axes.
 The angular field contains the angular velocities in the x, y, z axes.
 The covariance matrix parameters are linear and angular velocities in order.
For detailed info about the covariance matrix RMSE? Variances? Covariance Matrix?.
Acceleration
For this information, you can use the AccelWithCovarianceStamped message.
Its structure is as follows:

geometry_msgs/AccelWithCovarianceStamped
following fields are used:
std_msgs/Header
header 
geometry_msgs/AccelWithCovariance
accel
geometry_msgs/Accel
accel
geometry_msgs/Vector3
linear 
geometry_msgs/Vector3
angular


float64[36]
covariance


 The linear field contains the linear accelerations in the x, y, z axes.
 The angular field contains the angular accelerations in the x, y, z axes.
 The covariance matrix parameters are linear and angular accelerations in order.
For detailed info about the covariance matrix RMSE? Variances? Covariance Matrix?.
Design
Coordinate Frames
Frames used in Autoware are defined as follows:
flowchart LR
earth > Map[map] > base_link
base_link > gnss_ins
base_link > sensor_a
base_link > sensor_b
In Autoware, the earth
frame is mostly omitted, only used in the GnssInsPositionStamped
message.
The map
frame is used as the stationary reference frame.
The map
frame’s axes point to the East, North, Up directions as explained in Coordinate Axes Conventions.
The base_link
is the center of the rear axle of the vehicle.
Map[map] > base_link
is the main transformation that is attempted to be estimated by various localization modules. This transformation is output by the EKF(Extended Kalman Filter) localization module.
Other sensors’ frames are defined with respect to the base_link
frame in the vehicle.
Estimating the base_link
frame by using the other sensors
Generally we don’t have the localization sensors physically at the base_link
frame. So various sensors localize with respect to their own frames, let’s call it sensor
frame.
We introduce a new frame naming convention: x_by_y
:
x: estimated frame name
y: localization method/source
We cannot directly get the sensor
frame. Because we would need the EKF module to estimate the base_link
frame first.
Without the EKF module the best we can do is to estimate Map[map] > sensor_by_sensor > base_link_by_sensor
using this sensor.
Example by the GNSS/INS sensor
For the integrated GNSS/INS we use the following frames:
flowchart LR
earth > Map[map] > gnss_ins_by_gnss_ins > base_link_by_gnss_ins
The gnss_ins_by_gnss_ins
frame is obtained by the coordinates from GNSS/INS sensor. The coordinates are converted to map
frame using the gnss_poser
node.
Finally gnss_ins_by_gnss_ins
frame represents the position of the gnss_ins
estimated by the gnss_ins
sensor in the map
.
Then by using the static transformation between gnss_ins
and the base_link
frame, we can obtain the base_link_by_gnss_ins
frame. Which represents the base_link
estimated by the gnss_ins
sensor.
References:
Coordinate Axes Conventions
We are using East, North, Up (ENU) coordinate axes convention by default throughout the stack.
X+: East
Y+: North
Z+: Up
The position, orientation, velocity, acceleration are all defined in the same axis convention.
Position by the GNSS/INS sensor is expected to be in earth
frame.
Orientation, velocity, acceleration by the GNSS/INS sensor are expected to be in the sensor frame. Axes parallel to the map
frame.
If roll, pitch, yaw is provided, they correspond to rotation around X, Y, Z axes respectively.
Rotation around:
X+: roll
Y+: pitch
Z+: yaw
References:
RMSE? Variances? Covariance Matrix?
Definitions
RMSE: Root Mean Square Error is a measure of the differences between values predicted by a model or an estimator and the values observed.
Variance: Squared deviation of a random variable from its sample mean.
Covariance: A measure of the joint variability of two random variables.
Covariance Matrix: A square matrix giving the covariance between each pair of elements of a given random vector
Simplified usage in Autoware
RMSE² = Variance
A covariance matrix is of n
random variables is an n×n
matrix.
Covariance with itself is the variance of the random variable.
The diagonal elements of the covariance matrix are the variances of the random variables.
In Autoware, only these variance values are used, mostly in the RMSE form. The rest of the covariance matrix is not used, can be left 0.0
.
Example for TwistWithCovariance
This message contains the linear and angular velocities and the covariance matrix.
Let’s call RMSE values for these calculations as σ_x, σ_y, σ_z, σ_r, σ_p, σ_y
.
The covariance matrix can be constructed as follows:
σ_x  0  0  0  0  0 
0  σ_y  0  0  0  0 
0  0  σ_z  0  0  0 
0  0  0  σ_r  0  0 
0  0  0  0  σ_p  0 
0  0  0  0  0  σ_y 
In the message file, it is a float64[36]
array. We fill the indices at i*7, i:[0,6]
, making up 0,7,14,21,28,35
th indices of this array.
References:
 https://en.wikipedia.org/wiki/Rootmeansquare_deviation
 https://en.wikipedia.org/wiki/Variance#Biased_sample_variance
 https://en.wikipedia.org/wiki/Covariance#Covariance_with_itself
 https://en.wikipedia.org/wiki/Covariance_matrix
Q/A
 Why is position and orientation not combined as a PoseWithCovarianceStamped message?
 Modern GNSS/INS sensors provide both of these together but more affordable gnss only sensors might provide only position information.
 We separated them to allow if the INS sensor is separate, the orientation information can be extracted from there with aid of a magnetometer.
Changelog for package autoware_sensing_msgs
1.2.0 (20241001)
1.1.0 (20240510)
Wiki Tutorials
Package Dependencies
Deps  Name 

ament_cmake_auto  
rosidl_default_generators  
rosidl_default_runtime  
ament_lint_auto  
ament_lint_common  
geometry_msgs  
std_msgs 