Datasets and Supporting Materials for the MALIN-ANR 2019 Competition (French national research agency)

<p>This &quot;ZENODO deposit&quot; provides a multiple sensor dataset collected by the&nbsp;CyborgLOC&nbsp;team during the intermediate competition of the Challenge MALIN (<em>MA</em><em>&icirc;trise</em><em>&nbsp;de la&nbsp;</em><em>L</em><em>ocalisation&nbsp;</em><em>IN</em><em>door</em>), which is a competition for indoor/outdoor real-time positioning. The sensors, including a GNSS receiver&nbsp;Ublox&nbsp;NEO-M8N, a&nbsp;Realsense&nbsp;D435i stereo&nbsp;camera, three&nbsp;Xsens&nbsp;MTi-300&nbsp;and one PERSY (<strong>PE</strong>destrian&nbsp;<strong>R</strong>eference&nbsp;<strong>SY</strong>stem), are mounted on different parts of the subject&rsquo;s body. The PERSY is a foot-mounted positioning device with&nbsp;a&nbsp;tri-axial accelerometer, a tri-axial gyroscope,&nbsp;a tri-axial magnetometer as well as a GNSS receiver&nbsp;Ublox&nbsp;M8T. The two scenarios are designed in a training&nbsp;center&nbsp;of firefighters CFIS (Fire and Rescue Training&nbsp;Center) in Blois,&nbsp;France to simulate the situation of firefighters during interventions. With total distances around 2 km&nbsp;for each scenario, the&nbsp;travelled&nbsp;trajectories passed through&nbsp;challenging&nbsp;environments including indoor, outdoor, urban canyon. The&nbsp;indoor part contains different stair levels,&nbsp;from&nbsp;the&nbsp;underground up to&nbsp;the&nbsp;6th&nbsp;floor. The travel modes are vehicles&nbsp;and pedestrians. Several classical activities of firefighters are realized such as walking, running, stair-climbing, side-walking, crawling, passing above/below obstacles, carrying a stretcher, ladder climbing,&nbsp;etc. High accurate ground truth of&nbsp;stationary points and enclosing volumes are provided by the organizers of the competition, i.e., the&nbsp;French Ministry of&nbsp;Defense&nbsp;(DGA: Direction&nbsp;G&eacute;n&eacute;rale&nbsp;de&nbsp;l&rsquo;Armement). Provided with raw data, they&nbsp;allow the evaluation of the positioning performances.</p> <p>To facilitate the&nbsp;use&nbsp;of our dataset under&nbsp;Rosbag&nbsp;format, a toolkit of python scripts&nbsp;named&nbsp;<em>MALIN Data Processing Tools</em>&nbsp;is provided on&nbsp;GitHub&nbsp;(<a href="https://github.com/4g-group/malin_data_processing_tools">https://github.com/4g-group/malin_data_processing_tools</a>). It&nbsp;allows merging&nbsp;Rosbags, converting&nbsp;Rosbag&nbsp;files to&nbsp;CSV&nbsp;files as well as republishing camera&rsquo;s topics as decompressed data. Details&nbsp;about&nbsp;these&nbsp;processing tools&nbsp;could be found in the Readme file on the&nbsp;Github&nbsp;page.&nbsp;&nbsp;</p>