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The UTIAS multi-robot cooperative localization and mapping dataset

2011· article· en· 110 citations· W1981983914 on OpenAlex· 10.1177/0278364911398404

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

The three-model screen

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All three models called this out of scope.

stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: infrastructure/announcement
about Canada: no
confidence: medium

Descriptor for a multi-robot localization and mapping dataset; sharing a domain benchmark dataset is doing research, not studying data sharing, so it falls outside the metaresearch ecosystem despite being a resource paper.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

The paper presents a robotics dataset for use in research but does not study research infrastructure itself.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Robotics multi-robot localization and SLAM dataset for domain algorithms, not research practice.

Abstract

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/.

Stored with the screening record, where it is evidence for the labels above.

The record

Venue
The International Journal of Robotics Research
Topic
Robotics and Sensor-Based Localization
Field
Engineering
Canadian institutions
Institute for Christian StudiesUniversity of Toronto
Funders
Keywords
RobotSimultaneous localization and mappingComputer scienceArtificial intelligenceProcess (computing)Data collectionComputer visionData miningMobile robotMathematics
Has abstract in OpenAlex
yes