Code: COVINS

COVINS: A Framework for Collaborative Visual-​Inertial SLAM and Multi-​Agent 3D Mapping

COVINS is an accurate, scalable, and versatile visual-​inertial collaborative SLAM system, that enables a group of robotic agents (e.g. small drones) equipped with visual and inertial sensing, to simultaneously co-​localize and jointly map an environment. In this framework, each agent runs a Visual-​Inertial Odometry (VIO) algorithm onboard, sharing newly acquired map information with the server through the COVINS communication interface. The centralized server back-​end accumulates and maintains the data contributed by all agents, and joins any overlapping map data into a shared global SLAM estimate online during the mission. The COVINS server back-​end can run on a local PC or a remote cloud server, and provides a communication module that allows agents to dynamically join the collaborative SLAM estimation process, and to interface custom keyframe-​based VIO systems with COVINS to generate collaborative estimates.

The COVINS software is publicly available and can be accessed via link

Users of this software are asked to cite the following article, where it was introduced:

Patrik Schmuck, Thomas Ziegler, Marco Karrer, Jonathan Perraudin and Margarita Chli, "COVINS: Visual-​Inertial SLAM for Centralized Collaboration" in Proceedings of the IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2021.
(Research Collection)

The video below shows example experiments presented in this work. 

V4RL

The Vision for Robotics Laboratory focuses on robotic vision-based perception. The group works with small Unmanned Aerial Vehicles (UAVs) in particular, as they are some of the most challenging robotic platforms, however, our research can be applied on any robot in need of perceiving its motion and/or workspace.

Contact

LEE H 304
Vision for Robotics Lab, IRIS, D-MAVT
ETH Zurich
Leonhardstrasse 21
CH-8092 Zurich
Switzerland

Tel: +41 (0)44 632 0838
Fax: +41 (0)44 632 1181
Email: chlim (at) ethz.ch

© Copyright – V4RL 2024.
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