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ekf setup
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@rafal-gorecki
rafal-gorecki committed Oct 23, 2023
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112 changes: 45 additions & 67 deletions rosbot_bringup/config/ekf.yaml
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### ekf config file ###
# Ref: http://docs.ros.org/en/noetic/api/robot_localization/html/state_estimation_nodes.html

ekf_filter_node:
ros__parameters:
predict_to_current_time: false
frequency: 30.0
sensor_timeout: 0.06

frequency: 25.0
sensor_timeout: 0.1
two_d_mode: true
print_diagnostics: true
publish_tf: true

transform_time_offset: 0.0
transform_timeout: 0.1

map_frame: map
odom_frame: odom
base_link_frame: base_link
world_frame: odom
publish_tf: true
publish_acceleration: false

odom0: /rosbot_base_controller/odom
odom0_config: [false, false, false, # X , Y , Z
false, false, false, # roll , pitch ,yaw
true, true, false, # dX , dY , dZ
false, false, false, # droll , dpitch ,dyaw
false, false, false] # ddX , ddY , ddZ

odom0_queue_size: 10
odom0_nodelay: true
odom0_config: [false, false, false,
false, false, false,
true, true, false,
false, false, true,
false, false, false]
odom0_queue_size: 2
odom0_nodelay: false
odom0_differential: false
odom0_relative: false
odom0_relative: true

imu0: /imu_broadcaster/imu
imu0_config: [false, false, false, # X , Y , Z
false, false, true, # roll , pitch ,yaw
false, false, false, # dX , dY , dZ
false, false, false, # droll , dpitch ,dyaw
false, false, false] # ddX , ddY , ddZ
imu0_queue_size: 10
imu0_nodelay: true
imu0_config: [false, false, false,
false, false, false,
false, false, false,
false, false, true,
true, true, false]
imu0_queue_size: 5
imu0_nodelay: false
imu0_differential: false
imu0_relative: true
imu0_remove_gravitational_acceleration: true

# [ADVANCED] The process noise covariance matrix can be difficult to tune, and can vary for each application, so it is
# exposed as a configuration parameter. This matrix represents the noise we add to the total error after each
# prediction step. The better the omnidirectional motion model matches your system, the smaller these values can be.
# However, if users find that a given variable is slow to converge, one approach is to increase the
# process_noise_covariance diagonal value for the variable in question, which will cause the filter's predicted error
# to be larger, which will cause the filter to trust the incoming measurement more during correction. The values are
# ordered as x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Defaults to the matrix below if
# unspecified.
# Note: the specification of covariance matrices can be cumbersome, so all matrix parameters in this package support
# both full specification or specification of only the diagonal values.
process_noise_covariance: [0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.06, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.06, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.025, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.025, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.02, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.015]
reset_on_time_jump: false
predict_to_current_time: false
print_diagnostics: true

# [ADVANCED] This represents the initial value for the state estimate error covariance matrix. Setting a diagonal
# value (variance) to a large value will result in rapid convergence for initial measurements of the variable in
# question. Users should take care not to use large values for variables that will not be measured directly. The values
# are ordered as x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Defaults to the matrix below
#if unspecified.
initial_estimate_covariance: [1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 1e-8, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9]
# Selected values ​​experimentally so as to ensure relatively fast convergence (values ​​should be about 10x higher than the sensor variance values)
dynamic_process_noise_covariance: true
process_noise_covariance: [5e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 5e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 5e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 1e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 1e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 1e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3e-3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2e-4, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2e-4, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2e-4, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-5, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-5, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-5]
5 changes: 4 additions & 1 deletion rosbot_controller/config/diff_drive_controller.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,9 @@ imu_broadcaster:
ros__parameters:
sensor_name: imu
frame_id: imu_link
static_covariance_orientation: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
static_covariance_angular_velocity: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.8e-3] # Values measured experimentally
static_covariance_linear_acceleration: [6.4e-2, 0.0, 0.0, 2.2e-2, 0.0, 0.0, 0.0, 0.0, 0.0] # Values measured experimentally

rosbot_base_controller:
ros__parameters:
Expand All @@ -55,7 +58,7 @@ rosbot_base_controller:
odom_frame_id: odom
base_frame_id: base_link
pose_covariance_diagonal: [0.001, 0.001, 0.001, 0.001, 0.001, 0.01]
twist_covariance_diagonal: [0.001, 0.001, 0.001, 0.001, 0.001, 0.01]
twist_covariance_diagonal: [3.3e-5, 3.3e-5, 0.0, 0.0, 0.0, 2.8e-3] # Values measured experimentally

# Whether to use feedback or commands for odometry calculations
open_loop: false
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5 changes: 4 additions & 1 deletion rosbot_controller/config/mecanum_drive_controller.yaml
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Expand Up @@ -28,6 +28,9 @@ imu_broadcaster:
ros__parameters:
sensor_name: "imu"
frame_id: "imu_link"
static_covariance_orientation: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # Values measured experimentally
static_covariance_angular_velocity: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.8e-3] # Values measured experimentally
static_covariance_linear_acceleration: [6.4e-2, 0.0, 0.0, 2.2e-2, 0.0, 0.0, 0.0, 0.0, 0.0] # Values measured experimentally

rosbot_base_controller:
ros__parameters:
Expand All @@ -51,7 +54,7 @@ rosbot_base_controller:
odom_frame_id: odom
base_frame_id: base_link
pose_covariance_diagonal: [0.001, 0.001, 0.001, 0.001, 0.001, 0.01]
twist_covariance_diagonal: [0.001, 0.001, 0.001, 0.001, 0.001, 0.01]
twist_covariance_diagonal: [3.3e-5, 3.3e-5, 0.0, 0.0, 0.0, 2.8e-3] # Values measured experimentally

# Whether to use feedback or commands for odometry calculations
open_loop: false
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