MEMROC: Multi-Eye to Mobile RObot Calibration

TL;DR

MEMROC is a new calibration method for mobile robot cameras that uses a known pattern and ground plane detection to achieve accurate, robust, and easy calibration with minimal data, suitable for daily robot operation.

Contribution

It introduces MEMROC, a motion-based calibration approach that simplifies multi-camera calibration on mobile robots, addressing limitations of existing methods in dynamic environments.

Findings

Outperforms state-of-the-art calibration methods in accuracy

Demonstrates robustness to noisy odometry data

Requires fewer images for effective calibration

Abstract

This paper presents MEMROC (Multi-Eye to Mobile RObot Calibration), a novel motion-based calibration method that simplifies the process of accurately calibrating multiple cameras relative to a mobile robot's reference frame. MEMROC utilizes a known calibration pattern to facilitate accurate calibration with a lower number of images during the optimization process. Additionally, it leverages robust ground plane detection for comprehensive 6-DoF extrinsic calibration, overcoming a critical limitation of many existing methods that struggle to estimate the complete camera pose. The proposed method addresses the need for frequent recalibration in dynamic environments, where cameras may shift slightly or alter their positions due to daily usage, operational adjustments, or vibrations from mobile robot movements. MEMROC exhibits remarkable robustness to noisy odometry data, requiring minimal calibration input data. This combination makes it highly suitable for daily operations involving mobile robots. A comprehensive set of experiments on both synthetic and real data proves MEMROC's efficiency, surpassing existing state-of-the-art methods in terms of accuracy, robustness, and ease of use. To facilitate further research, we have made our code publicly available at https://github.com/davidea97/MEMROC.git.