Bearing only cooperative localization has been used successfully on aerial and ground vehicles. In this paper we present an extension of the approach to the underwater domain. The focus is on adapting the technique to handle the challenging visibility conditions underwater. Furthermore, data from inertial, magnetic, and depth sensors are utilized to improve the robustness of the estimation. In addition to robotic applications, the presented technique can be used for cave mapping and for marine archeology surveying, both by human divers. Experimental results from different environments, including a fresh water, low visibility, lake in South Carolina; a cavern in Florida; and coral reefs in Barbados during the day and during the night, validate the robustness and the accuracy of the proposed approach.
This paper presents a two-dimensional multi-robot cooperative localization and mapping dataset collection for research and educational purposes. The dataset consists of nine sub-datasets, which can be used for studying problems such as robot-only cooperative localization, cooperative localization with a known map, and cooperative simultaneous localization and mapping (SLAM) . The data collection process is discussed in detail, including the equipment we used, how measurements were made and logged, and how we obtained groundtruth data for all robots and landmarks. The format of each file in each sub-dataset is also provided. The dataset is available for download at http://asrl.utias.utoronto.ca/datasets/mrclam/.
Berzelius failed to make use of Faraday's electrochemical laws in his laborious determination of equivalent weights.