一、误差

内容取自 TUM数据集：
https://vision.in.tum.de/data/datasets/rgbd-dataset/tools

The ATE is well-suited for measuring the performance of visual SLAM systems. In contrast, the RPE is well-suited for measuring the drift of a visual odometry system, for example the drift per second.
脚本代码下载链接：
https://vision.in.tum.de/data/datasets/rgbd-dataset/tools

1.1 ABSOLUTE TRAJECTORY ERROR (ATE)

The absolute trajectory error directly measures the difference between points of the true and the estimated trajectory. As a pre-processing step, we associate the estimated poses with ground truth poses using the timestamps. Based on this association, we align the true and the estimated trajectory using singular value decomposition. Finally, we compute the difference between each pair of poses, and output the mean/median/standard deviation of these differences. Optionally, the script can plot both trajectories to a png or pdf file.

1.2 RELATIVE POSE ERROR (RPE)

For computing the relative pose error, we provide a script ‘‘evaluate_rpe.py’’. This script computes the error in the relative motion between pairs of timestamps. By default, the script computes the error between all pairs of timestamps in the estimated trajectory file. As the number of timestamp pairs in the estimated trajectory is quadratic in the length of the trajectory, it can make sense to downsample this set to a fixed number (–max_pairs). Alternatively, one can choose to use a fixed window size (–fixed_delta). In this case, each pose in the estimated trajectory is associated with a later pose according to the window size (–delta) and unit (–delta_unit). This evaluation technique is useful for estimating the drift.

1.3 ABSOLUTE POSE ERROR (APE)

二、EVO工具

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SLAM ---- 误差测评 ATE、RPE、APE，与EVO

SLAM ---- 误差测评 ATE、RPE，与EVO