process has died

[Luca1125ly]

could you tell me how to solve this problem? And the following is my gvins.yaml:

IC-GVINS多源融合定位算法配置文件

结果输出路径

Output directory

outputpath: "/home/liuyong/gvins_ws/result/" is_make_outputdir: true

时间信息, s

Time length for GNSS/INS intialization

initlength: 1

IMU原始数据频率, Hz

IMU sample rate

imudatarate: 200

考虑地球自转补偿项

Consider the Earth rotation

iswithearth: true

天线杆臂, IMU前右下方向, m

GNSS lever-arm in IMU body frame (front-right-down)

antlever: [-0.37, 0.008, 0.353]

antlever: [-0.52, 0.000, 0.000]

IMU噪声建模参数

IMU noise parameters

imumodel:

arw: 0.1 # deg/sqrt(hr)

 arw: 0.00015641921981365443

vrw: 0.1 # m/s/sqrt(hr)

 vrw: 0.0007853161973805388

gbstd: 50.0 # deg/hr

 gbstd: 5.837129494278657e-05

abstd: 50.0 # mGal

 abstd: 3.2064659601889169e-04 
corrtime: 1.0   # hr

GNSS中断配置

GNSS outage configurations, the GNSS will not be used after the gnssoutagetime

isusegnssoutage: false

gnssoutagetime: 0

gnssoutagetime: 364461.5

固定阈值GNSS抗差

A fixed threshold (STD, m) for GNSS outlier culling

gnssthreshold: 20

是否开启可视化

Use visualization

is_use_visualization: true

跟踪

Tracking configurations

track_check_histogram: false # 直方图检查, 避免出现光照变化较大的图像 (Check histogram for drastic illumulation change) track_min_parallax: 20 # 关键帧最小像素视差 (The minmum parallax in pixels to choose a keyframe) track_max_interval: 0.5 # 最大的关键帧间隔, 超过则插入观测帧, s (The maximum lenght to choose a observation frame) track_max_features: 200 # 最大提取特征数量 (The maximum features to detect, may be more or less, see tracking.cc)

优化

Optimization configurations

reprojection_error_std: 1.5 # 像素重投影误差 (The reprojection error std for optimizition and outlier culling) optimize_windows_size: 10 # 滑动窗口大小 (The size of the sliding window, number of the keyframes ) optimize_num_iterations: 20 # 优化迭代次数 (The iterations in total) optimize_estimate_extrinsic: true # 是否估计相机和IMU的外参 (Estimate the extrinsic) optimize_estimate_td: true # 否估计相机和IMU之间的时间间隔 (Estimate the time delay)

Camera parameters

cam0:

内参 [fx, fy, cx, cy(, skew)]

# Intrinsic parameters, pinhole model
#intrinsic: [787.1611861559479, 787.3928431375225, 664.4061078354368, 519.5129292754456]
 intrinsic: [519.1029197155882, 515.6197310158666, 337.4581737211765, 246.2314274977031]
# 畸变参数 [k1, k2, p1, p2(, k3)]
# Distortion parameters
#distortion: [-0.0917403092279957, 0.08134715036932794, 0.00017620136958692255, 0.00016737385248865412]
 distortion: [-0.015230266432204792, -0.014585751011126085, 0.004316174021897651, 0.005858538434865227]
# 图像分辨率
# Resolution
#resolution: [1278, 1022]
 resolution: [640, 480]
# 相机IMU外参 (Camera-IMU extrinsic)
# Pb = q_b_c * Pc + t_b_c
# q (x, y, z, w)
#q_b_c: [0.497766, 0.502679, 0.501396, 0.498141]
#t_b_c: [0.074, -0.030, 0.128]
q_b_c: [0.498, 0.502, 0.501, 0.498]
t_b_c: [-0.088, -4.668, 0.148]
# IMU和相机时间延时 (The time delay between the IMU and camera)
# t_i = t_c + td
#td_b_c: 0.0
td_b_c: -0.005256070059517965