A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry

In this tutorial, we provide principled methods to quantitatively evaluate the quality of an estimated trajectory from visual(-inertial) odometry (VO/VIO), which is the foundation of benchmarking the accuracy of different algorithms. First, we show how to determine the transformation type to use in trajectory alignment based on the specific sensing modality (i.e., monocular, stereo and visual-inertial). Second, we describe commonly used error metrics (i.e., the absolute trajectory error and the relative error) and their strengths and weaknesses. To make the methodology presented for VO/VIO applicable to other setups, we also generalize our formulation to any given sensing modality. To facilitate the reproducibility of related research, we publicly release our implementation of the methods described in this tutorial.

Published in:
Presented at:
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain , 1-5 October 2018
Jan 07 2019
Open Source Code: A trajectory evaluation toolbox that implements the methods in this tutorial is available at https://github.com/uzh-rpg/rpg_trajectory_evaluation.
Other identifiers:

 Record created 2019-10-31, last modified 2019-11-06

Rate this document:

Rate this document:
(Not yet reviewed)