一种评估SLAM系统参数的实用工具

一种评估SLAM系统参数的实用工具

evo是一款Python版本SLAM系统的评估工具,其简单可用,下面是使用evo评估VIORB示例


具体使用细节总结如下:

用来评估SLAM系统测量数据以及输出估计优劣的Pyrhon工具

安装:

pip install evo --upgrade --no-binary evo

适用于数据集有:

TUM 轨迹文件

KITTI 位姿

EUROC .csv和.txt文件

ROS bag文件

关于数据格式:



具体用法:

(1)evo_traj euroc data.csv --plot

可直接输出 name: data

infos: 36382 poses, 80.626m path length, 181.905s duration

以及 trajectory xyz_view rpy_view 随时间变化的曲线图


(2)evo_traj euroc data.csv --save_as_tum

--save_as_bag

--save_as_kitti

保存为data.tum格式


(3)evo_ape (绝对位姿误差)evo_rpe(相对位姿误差) evo_rpe euroc --help

绝对位姿误差,常作为绝对轨迹误差使用。通过姿态关系直接估计和参考对应姿态。然后,计算整个轨迹的统计数据。这对于测试轨迹的全局一致性是有用的。


相对于绝对姿态的直接比较,相对姿态误差比较运动(“姿态三角”)。该度量给出了关于局部精度的见解,即漂移。例如,可以评估每米的平移或旋转漂移:


一般模式: command format reference-trajectory estimated-trajectory [options]

e.g evo_ape euroc data00.csv SaveTrajectory0.txt -va --plot --save_results ./result/ORB.ZIP

e.g evo_rpe tum reference.txt estimate.txt --pose_relation angle_deg --delta 1 --delta_unit m


bag模式:command bag bagfile-path reference-topic estimated-topic [options]


(4)绘制不同算法(ORB PTAM等)中与真实轨迹的图

evo_traj kitti KITTI_00_ORB.txt KITTI_00_SPTAM.txt --ref=KITTI_00_gt.txt -p --plot_mode=xz


(5)调整显示尺寸

evo_config set plot_figsize 5 4.5

evo_config reset 恢复默认设置


(6)处理不同结果

*First trajectory (ORB Stereo):*

mkdir results

evo_ape kitti KITTI_00_gt.txt KITTI_00_ORB.txt -va --plot --plot_mode xz --save_results results/ORB.zip


*Second trajectory (S-PTAM):*

evo_ape kitti KITTI_00_gt.txt KITTI_00_SPTAM.txt -va --plot --plot_mode xz --save_results results/SPTAM.zip


Here, we use the results from above to generate a plot and a table:

evo_res results/*.zip -p --save_table results/table.csv


自己实测显示结果:


--------------------------------------------------------------------------------

Forcing trajectory alignment implicitly (EuRoC ground truth is in IMU frame).

--------------------------------------------------------------------------------

Loaded 36382 stamps and poses from: data.csv

Loaded 3676 stamps and poses from: SaveTrajectory.txt

Synchronizing trajectories...

Found 3638 of max. 36382 possible matching timestamps between...

data.csv

and: SaveTrajectory.txt

..with max. time diff.: 0.01 (s) and time offset: 0.0 (s).

--------------------------------------------------------------------------------

Aligning using Umeyama's method...

Rotation of alignment:

[[-0.34671241 -0.88295882 0.31650314]

[-0.93757415 0.31641858 -0.14433985]

[ 0.02729867 -0.34678958 -0.93754561]]

Translation of alignment:

[ 4.78431507 -1.95239101 0.86022843]

Scale correction: 1.0

--------------------------------------------------------------------------------

Compared 3638 absolute pose pairs.

Calculating APE for translation part pose relation...

--------------------------------------------------------------------------------

APE w.r.t. translation part (m)

(with SE(3) Umeyama alignment)


max 0.361395

mean 0.163031

median 0.179523

min 0.023681

rmse 0.180996

sse 119.178913

std 0.078616


--------------------------------------------------------------------------------

Plotting results...



发布于 2018-11-01 16:38