MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System

TL;DR

This paper introduces MultiCol-SLAM, a real-time, modular multi-camera SLAM system that extends existing methods to multi-camera setups, demonstrating improved robustness and accuracy over single-camera systems.

Contribution

It presents a novel multi-camera SLAM system based on the MultiCol model, extending state-of-the-art SLAM to arbitrary rigidly coupled multi-camera configurations.

Findings

Enhanced robustness compared to single-camera SLAM

Accurate pose estimation with ground truth validation

Open source implementation available online

Abstract

The basis for most vision based applications like robotics, self-driving cars and potentially augmented and virtual reality is a robust, continuous estimation of the position and orientation of a camera system w.r.t the observed environment (scene). In recent years many vision based systems that perform simultaneous localization and mapping (SLAM) have been presented and released as open source. In this paper, we extend and improve upon a state-of-the-art SLAM to make it applicable to arbitrary, rigidly coupled multi-camera systems (MCS) using the MultiCol model. In addition, we include a performance evaluation on accurate ground truth and compare the robustness of the proposed method to a single camera version of the SLAM system. An open source implementation of the proposed multi-fisheye camera SLAM system can be found on-line https://github.com/urbste/MultiCol-SLAM.