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UAV1_params.yaml
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UAV1_params.yaml
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###########################
# Initial state estimates #
###########################
# Calascio ruin UAV 1 starting pose
# p: [0.0996536944321, 0.650105327481, 0.485353333074] # [x,y,z]
# v: [0.013064551, -0.677197571, 0.510333198] # [x,y,z]
# q: [0.999476479566, -0.02852409305, 0.0150073484925, -0.00281467611065] # [w,x,y,z]
# INVERARAY PARALLEL
# p: [-11.0238324478,5.87781035059,4.97533455791] # [x,y,z]
# v: [-0.91143948, 0.2073374, -0.136389114] # [x,y,z]
# q: [0.998285779503,0.0242414304708,0.0528674363413,0.00654902012466] # [w,x,y,z]
# INVERARAY AROUND
p: [-41.1312907116, -0.00688860865911, 1.10769421553] # [x,y,z]
v: [-0.74676504, 0.02250653, -0.15494689] # [x,y,z]
q: [0.999642286845, 0.00442585804707, 0.0261189530978, -0.00367565232272] # [w,x,y,z]
# Mars sol 180
# p: [-1.30295832, 0.5750514, 0.78614989]
# v: [-0.5741264 , -0.4824844, 0.09578103]
# q: [0.999397457339, -0.014541623862, 0.014590109983, 0.0279354994628]
# Initial IMU bias estimates
b_w: [0.0, 0.0, 0.0] # [x,y,z]
b_a: [0.0, 0.0, 0.0] # [x,y,z]
# Initial standard deviation estimates [x,y,z]
sigma_dp: [0.0, 0.0, 0.0] # [m]
sigma_dv: [0.05, 0.05, 0.05] # [m/s]
sigma_dtheta: [3.0, 3.0, 3.0] # [deg]
sigma_dbw: [6.0, 6.0, 6.0] # [deg/s]
sigma_dba: [0.3, 0.3, 0.3] # [m/s^2]
###############
# Calibration #
###############
# VI Simulator
cam1_fx: 0.605053191
cam1_fy: 0.947916667
cam1_cx: 0.5000
cam1_cy: 0.5000
cam1_s: 0.0
cam1_img_width: 752
cam1_img_height: 480
cam1_q_ic: [0.004059133072894, -0.928890463133302, -0.370065735566358, 0.014049352983967] # [w,x,y,z]
cam1_p_ic: [0.05914814, -0.04309647, 0.03085167] # [x,y,z]
cam1_time_offset: -0.000000001
# Feature noise (normalized coordinate standard deviation)
# 8.75/(cam_1fx)/cam1_img_width
sigma_img: 0.011307696 # sqrt(0.00012922762474977756 * 5.0)
#######
# IMU #
#######
# ADIS16448 accels (Astec)
n_a: 0.004 # Accel noise spectral density [m/s^2/sqrt(Hz)]
n_ba: 0.006 # Accel bias random walk [m/s^3/sqrt(Hz)]
# ADIS16448 gyros (Astec)
n_w: 0.0003394 # Gyro noise spectral density [rad/s/sqrt(Hz)]
n_bw: 0.000038785 # Gyro bias random walk [rad/s^2/sqrt(Hz)]
#######
# LRF #
#######
# Noise (standard deviation in m)
sigma_range: 0.05
##############
# Sun Sensor #
##############
# Currently unused
q_sc: [1.0, 0.0, 0.0, 0.0] # [w,x,y,z]
w_s: [0.0, 0.0, 1.0] # [x,y,z]
###########
# Tracker #
###########
#0-based maximal pyramid level number; if set to 0, pyramids are not used (single level),
# if set to 1, two levels are used, and so on; if pyramids are passed to input then
# algorithm will use as many levels as pyramids have but no more than maxLevel.
max_level: 2
# The algorithm calculates the minimum eigen value of a 2x2 normal matrix of optical
# flow equations (this matrix is called a spatial gradient matrix in [25]), divided
# by number of pixels in a window; if this value is less than minEigThreshold, then
# a corresponding feature is filtered out and its flow is not processed, so it allows
# to remove bad points and get a performance boost.
min_eig_thr: 0.0
# Size of the search window at each pyramid level.
win_size_w: 31
win_size_h: 31
fast_detection_delta: 20
non_max_supp: True
block_half_length: 20
margin: 20
n_feat_min: 400
# RANSAC: 8 / LMEDS: 4 (see OpenCV doc)
outlier_method: 8
# Parameter used for RANSAC. It is the maximum distance from a point to an epipolar line in pixels,
# beyond which the point is considered an outlier and is not used for computing the final fundamental
# matrix. It can be set to something like 1-3, depending on the accuracy of the point localization,
# image resolution, and the image noise.
outlier_param1: 0.3
# Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of confidence
# (probability) that the estimated matrix is correct.
outlier_param2: 0.99
# 1 <=> no tiling
n_tiles_h: 3 # 3 INV AROUND same for PARALLEL
n_tiles_w: 3 # 3 INV AROUND same for PARALLEL
max_feat_per_tile: 10000
##############
# SLAM-MSCKF #
##############
# Number of poses in the sliding window
n_poses_max: 15
# Number of SLAM features
n_slam_features_max: 15
# Initial inverse depth of SLAM features [1/m]
# (default: 1 / (2 * d_min) [Montiel, 2006])
# rho_0: 0.25 # CIRCLE LOW START
# rho_0: 0.043751393601 # INVERARAY SPARSE
# rho_0: 0.0303825167012 # INVERARAY PARALLEL
# rho_0: 0.371576345786 # Mars Sol 180
rho_0: 0.1 # INVERARAY AROUND
# Initial standard deviation of SLAM inverse depth [1/m]
# (default: 1 / (4 * d_min) [Montiel, 2006])
# sigma_rho_0: 0.125 # CIRCLE LOW START
# sigma_rho_0: 0.021875697 # INVERARAY SPARSE
# sigma_rho_0: 0.015191258 # INVERARAY PARALLEL
# sigma_rho_0: 0.185788173 # Mars Sol 180
sigma_rho_0: 0.05 # INVERARAY AROUND
# Number of IEKF iterations (1 <=> EKF)
iekf_iter: 1
# Minimum baseline to trigger MSCKF measurement (pixels)
msckf_baseline: 30.0
# Minimum track length for a visual feature to be processed
min_track_length: 15
########################
# MULTI UAV PARAMETERS #
########################
pr_desc_ratio_thr: 0.75
pr_desc_min_distance: 50.0
desc_type: 0 # DESCRIPTOR_TYPE { ORB=0 };
sigma_landmark: 0.02 # meters
descriptor_scale_factor: 1.2
descriptor_pyramid: 8
descriptor_patch_size: 51
pr_score_thr: 0.65
ci_msckf_w: 0.015 # INV PARALLEL # Covariance intersection weight of the other UAVs. if < 0 it's going to perform the optimization problem.
ci_slam_w: 0.05 # INV PARALLEL # Covariance intersection weight of the other UAVs. if < 0 it's going to perform the optimization problem.
# BoW ORB vocabulary
# vocabulary_path: '/home/viciopoli/JPL/devel/x_ws/src/x/Vocabulary/orb_thermal_voc.fbow' # Thermal voc must be a fbow
vocabulary_path: '/home/viciopoli/JPL/devel/x_ws/src/x/Vocabulary/visual_voc_3_4_dbow3.yaml' #
# vocabulary_path: '/code/catkin_ws/src/x-image/packages/x/Vocabulary/orb_mur.fbow' # this must be a .tar.gz file
########
# Misc #
########
# Gravity vector in world frame [m/s^2]
g: [0.0, 0.0, -9.81] # [x,y,z]
# state buffer size
state_buffer_size: 250
# Timeout before 3D trajectory disappears in GUI (s)
traj_timeout_gui: 3
# flags to play rosbags
/use_sim_time: True
# Initialize at startup
init_at_startup: True