Difference between revisions of "Benchmark dataset for evaluation of range-based people tracker classifiers in mobile robots"

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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_03_1.bag env2_test_03_1.bag]: '''duration:''' 39.9s, '''size:''' 10.4 MB, '''start date/time:''' Nov 20, 2017 13:27:25.50
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_03_1.bag test_03_1.bag]: '''duration:''' 55.2s, '''size:''' 14.5 MB, '''start date/time:''' Nov 16 2017 12:43:58.29
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_03_2.bag env2_test_03_2.bag]: '''duration:''' 39.1s, '''size:''' 10.2 MB, '''start date/time:''' Nov 20, 2017 13:28:56.41
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_03_2.bag test_03_2.bag]: '''duration:''' 44.4s, '''size:''' 10.2 MB, '''start date/time:''' Nov 16 2017 12:46:31.99
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_03_3.bag env2_test_03_3.bag]: '''duration:''' 40.5s, '''size:''' 10.5 MB, '''start date/time:''' Nov 20, 2017 13:30:04.94
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_03_3.bag test_03_3.bag]: '''duration:''' 51.1s, '''size:''' 13.4 MB, '''start date/time:''' Nov 16 2017 12:47:29.66
  
 
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* Scenario 04  (4 files):
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_10.bag env2_test_10.bag]: '''duration:''' 16:05s, '''size:''' 246.6 MB, '''start date/time:''' Nov 20, 2017 13:07:40.16
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_10.bag test_10.bag]: '''duration:''' 16:05s, '''size:''' 246.6 MB, '''start date/time:''' Nov 22 2017 11:55:02.39
  
 
* Scenario 11  (1 file):
 
* Scenario 11  (1 file):
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_11.bag env2_test_11.bag]: '''duration:''' 03:25s, '''size:''' 52.8 MB, '''start date/time:''' Nov 22 2017 13:08:11.99
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_11.bag test_11.bag]: '''duration:''' 03:25s, '''size:''' 52.8 MB, '''start date/time:''' Nov 22 2017 13:08:11.99
  
 
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* Scenario 12  (3 files):
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_14.bag env2_test_14.bag]: '''duration:''' 06:17s, '''size:''' 96.3 MB, '''start date/time:''' Nov 22 2017 12:23:07.92
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# [http://robotica.unileon.es/~datasets/LegTracking/v1.0/test_14.bag test_14.bag]: '''duration:''' 06:17s, '''size:''' 96.3 MB, '''start date/time:''' Nov 22 2017 12:23:07.92
  
 
====Scenario 3. Bedroom====
 
====Scenario 3. Bedroom====

Revision as of 12:32, 1 December 2017

SciCrunch! reference: Range-based people tracker classifiers Benchmark Dataset, RRID:SCR_015743.

This data report summarizes a benchmark dataset which can be used to evaluate the performance of different approaches for detecting and tracking people by using lidar sensors. Information contained at the dataset is specially suitable to be used as training data for neural network-based classifiers. Data have been gathered in an indoor mock-up apartment, shown in Fig 1 (B), located at the Robotics Lab of the University of León (Spain). An autonomous robot, called Orbi-One and shown in Fig 1 (A), with an on-board Real Time Location System (RTLS) was used to gather the data.

Materials

Data gathered by Orbi-One robot include:

  • Lidar sensor measures.
  • Location estimates from two people trackers: ROS-LD and PeTra.
  • People location provided by a commercial RTLS, called KIO, which can be used as ground-truth.
  • Some other useful data gathered by the Orbi-One robot such as map information, odometry, and transform data.

Additional information about Orbi-One and the devices/packages used to get data is given below.

Orbi-one

Orbi-One, shown at Fig 1 (A), is an assistant robot manufactured by Robotnik. The software to control the robot hardware is based on ROS.

File:PeopleTrackingFig1.png
Fig. 1: From left to right: (A) Orbi-One carrying KIO tag and a KIO anchor attached in the ceiling; (B) tobotics mobile lab plane, red dots show the location of KIO anchors; (C) occupancy map generated using lidar sensor measures; and (D) Network output.

KIO RTLS

KIO RTLS commercial solution by Eliko has been used to provide people location at the study area.

ROS Leg Detector (ROS-LD)

ROS-LD is a ROS package which takes messages published by a lidar sensor as input and uses a machine-learning-trained classifier to detect groups of laser readings as possible legs. The code is available in a public repository, but is unsupported at this time.

PeTra

PeTra is a people tracker tool for detecting and tracking people developed by the Robotics Group from the University of León.

Recording procedure

The data were gathered under 14 different scenarios. In all of them, Orbi-One was standing still as one or more people, carrying a KIO tag, moved around him. Fig. 2 shows the 14 different recognition scenarios recorded. These scenarios have been chosen according to different situations that may occurs on robotics competitions such as ERL or RoboCup.


Fig. 2: recognition scenarios recorded.

Data

A rosbag file was created for each scenario (3 for scenarios 3 and 12), recording lidar sensor measures, location estimates from PeTra and ROS-LD, locations from KIO RTLS and other useful data. Specifically, the following data were included in the rosbag files:

  • Laser sensor messages (sensor\_msgs/LaserScan) published at the /scan topic.
  • Location estimates calculated by PeTra published at the /person topic.
  • Location estimates calculated by ROS-LD at the /people\_tracker\_measurements topic.
  • Location estimates calculated by the KIO RTLS published at the /kio/PointStamped/4037/out topic.
  • Messages from the /map, /odom, and /tf topics which includes map information, odometry of the robot base, and transform information respectively.

Differents versions of the dataset are enumerated below.

v1.0 [Nov-2017]

Scenario 1. Kitchen

As a result of applying the recording method explained above, a first version of the dataset have been released. It includes measures for the scenarios defined at Fig. 2.:

  • Scenario 01 (1 file):
  1. test_01.bag: duration: 14:56s, size: 227.8 MB, start date/time: Jul 20, 2017 12:49:21.16
  • Scenario 02 (1 file):
  1. test_02.bag: duration: 15:08s, size: 233.0 MB, start date/time: Jul 26, 2017 11:01:24.72
  • Scenario 03 (3 files):
  1. test_03_1.bag: duration: 39.9s, size: 10.4 MB, start date/time: Jul 20, 2017 13:27:25.50
  2. test_03_2.bag: duration: 39.1s, size: 10.2 MB, start date/time: Jul 20, 2017 13:28:56.41
  3. test_03_3.bag: duration: 40.5s, size: 10.5 MB, start date/time: Jul 20, 2017 13:30:04.94
  • Scenario 04 (4 files):
  1. test_04_1.bag: duration: 58.3s, size: 15.0 MB, start date/time: Jul 25, 2017 10:39:52.62
  2. test_04_2.bag: duration: 57.2s, size: 14.7 MB, start date/time: Jul 25, 2017 10:41:16.31
  3. test_04_3.bag: duration: 50.5s, size: 13.0 MB, start date/time: Jul 25, 2017 10:42:44.95
  4. test_04_4.bag: duration: 1:01s, size: 15.7 MB, start date/time: Jul 25, 2017 10:43:52.44
  • Scenario 05 (1 file):
  1. test_05.bag: duration: 15:15s, size: 236.8 MB, start date/time: Jul 26, 2017 11:33:13.31
  • Scenario 06 (1 file):
  1. test_06.bag: duration: 09:18s, size: 143.3 MB, start date/time: Jul 26, 2017 12:25:45.12
  • Scenario 07 (1 file):
  1. test_07.bag: duration: 4:16s, size: 65.1 MB, start date/time: Jul 25, 2017 11:40:01.65
  • Scenario 08 (1 file):
  1. test_08.bag: duration: 03:39s, size: 55.8 MB, start date/time: Jul 25, 2017 12:25:29.22
  • Scenario 09 (5 files):
  1. test_09_1.bag: duration: 22.9s, size: 6.1 MB, start date/time: Jul 25, 2017 10:50:02.95
  2. test_09_2.bag: duration: 20.8s, size: 5.6 MB, start date/time: Jul 25, 2017 10:51:02.62
  3. test_09_3.bag: duration: 34.3s, size: 9.0 MB, start date/time: Jul 25, 2017 10:51:45.96
  4. test_09_4.bag: duration: 29.3s, size: 7.9 MB, start date/time: Jul 25, 2017 10:52:51.24
  5. test_09_5.bag: duration: 36.9s, size: 9.7 MB, start date/time: Jul 25, 2017 10:54:00.13
  • Scenario 10 (1 file):
  1. test_10.bag: duration: 15:50s, size: 240.5 MB, start date/time: Jul 20, 2017 13:07:40.16
  • Scenario 11 (1 file):
  1. test_11.bag: duration: 03:50s, size: 58.7 MB, start date/time: Jul 25, 2017 11:48:33.90
  • Scenario 12 (3 files):
  1. test_12_1.bag: duration: 43.6s, size: 11.3 MB, start date/time: Jul 20, 2017 13:33:23.74
  2. test_12_2.bag: duration: 44.3s, size: 11.5 MB, start date/time: Jul 20, 2017 13:34:24.95
  3. test_12_3.bag: duration: 37.3s, size: 9.7 MB, start date/time: Jul 20, 2017 13:35:31.55
  • Scenario 13 (3 files):
  1. test_13_1.bag: duration: 57.8s, size: 14.9 MB, start date/time: Jul 25, 2017 11:01:15.23
  2. test_13_2.bag: duration: 59.9s, size: 15.4 MB, start date/time: Jul 25, 2017 11:02:37.85
  3. test_13_3.bag: duration: 54.0s, size: 13.9 MB, start date/time: Jul 25, 2017 11:04:30.69
  • Scenario 14 (1 file):
  1. test_14.bag: duration: 05.57s, size: 90.5 MB, start date/time: Jul 25, 2017 11:10:32.97


Scenario 2. Living room

As a result of applying the recording method explained above, a first version of the dataset have been released in a second environment shown at Fig. 3. It also includes measures for the scenarios defined at Fig. 2.:

  • Scenario 01 (1 file):
  1. test_01.bag: duration: 15:37s, size: 239.7 MB, start date/time: Nov 16 2017 12:20:19.65
  • Scenario 02 (1 file):
  1. test_02.bag: duration: 15:05s, size: 231.4 MB, start date/time: Nov 27 2017 18:32:24.35
  • Scenario 03 (3 files):
  1. test_03_1.bag: duration: 55.2s, size: 14.5 MB, start date/time: Nov 16 2017 12:43:58.29
  2. test_03_2.bag: duration: 44.4s, size: 10.2 MB, start date/time: Nov 16 2017 12:46:31.99
  3. test_03_3.bag: duration: 51.1s, size: 13.4 MB, start date/time: Nov 16 2017 12:47:29.66
  • Scenario 04 (4 files):
  1. env2_test_04_1.bag: duration: 58.3s, size: 15.0 MB, start date/time: Nov 25, 2017 10:39:52.62
  2. env2_test_04_2.bag: duration: 57.2s, size: 14.7 MB, start date/time: Nov 25, 2017 10:41:16.31
  3. env2_test_04_3.bag: duration: 50.5s, size: 13.0 MB, start date/time: Nov 25, 2017 10:42:44.95
  4. env2_test_04_4.bag: duration: 1:01s, size: 15.7 MB, start date/time: Nov 25, 2017 10:43:52.44
  • Scenario 05 (1 file):
  1. test_05.bag: duration: 15:07s, size: 232.4 MB, start date/time: Nov 28 2017 18:33:16.24
  • Scenario 06 (1 file):
  1. test_06.bag: duration: 09:14s, size: 136.2 MB, start date/time: Nov 29 2017 13:12:42.61
  • Scenario 07 (1 file):
  1. test_07.bag: duration: 4:39s, size: 71.5 MB, start date/time: Nov 22 2017 12:48:33.86
  • Scenario 08 (1 file):
  1. test_08.bag: duration: 03:04s, size: 47.2 MB, start date/time: Nov 22 2017 12:59:08.58
  • Scenario 09 (5 files):
  1. env2_test_09_1.bag: duration: 22.9s, size: 6.1 MB, start date/time: Nov 25, 2017 10:50:02.95
  2. env2_test_09_2.bag: duration: 20.8s, size: 5.6 MB, start date/time: Nov 25, 2017 10:51:02.62
  3. env2_test_09_3.bag: duration: 34.3s, size: 9.0 MB, start date/time: Nov 25, 2017 10:51:45.96
  4. env2_test_09_4.bag: duration: 29.3s, size: 7.9 MB, start date/time: Nov 25, 2017 10:52:51.24
  5. env2_test_09_5.bag: duration: 36.9s, size: 9.7 MB, start date/time: Nov 25, 2017 10:54:00.13
  • Scenario 10 (1 file):
  1. test_10.bag: duration: 16:05s, size: 246.6 MB, start date/time: Nov 22 2017 11:55:02.39
  • Scenario 11 (1 file):
  1. test_11.bag: duration: 03:25s, size: 52.8 MB, start date/time: Nov 22 2017 13:08:11.99
  • Scenario 12 (3 files):
  1. env2_test_12_1.bag: duration: 43.6s, size: 11.3 MB, start date/time: Nov 20, 2017 13:33:23.74
  2. env2_test_12_2.bag: duration: 44.3s, size: 11.5 MB, start date/time: Nov 20, 2017 13:34:24.95
  3. env2_test_12_3.bag: duration: 37.3s, size: 9.7 MB, start date/time: Nov 20, 2017 13:35:31.55
  • Scenario 13 (3 files):
  1. env2_test_13_1.bag: duration: 57.8s, size: 14.9 MB, start date/time: Nov 25, 2017 11:01:15.23
  2. env2_test_13_2.bag: duration: 59.9s, size: 15.4 MB, start date/time: Nov 25, 2017 11:02:37.85
  3. env2_test_13_3.bag: duration: 54.0s, size: 13.9 MB, start date/time: Nov 25, 2017 11:04:30.69
  • Scenario 14 (1 file):
  1. test_14.bag: duration: 06:17s, size: 96.3 MB, start date/time: Nov 22 2017 12:23:07.92

Scenario 3. Bedroom

As a result of applying the recording method explained above, a first version of the dataset have been released in a third environment shown at Fig. 3. It also includes measures for the scenarios defined at Fig. 2.:

  • Scenario 01 (1 file):
  1. env3_test_01.bag: duration: 14:56s, size: 227.8 MB, start date/time: Nov 20, 2017 12:49:21.16
  • Scenario 02 (1 file):
  1. env3_test_02.bag: duration: 15:08s, size: 233.0 MB, start date/time: Nov 26, 2017 11:01:24.72
  • Scenario 03 (3 files):
  1. env3_test_03_1.bag: duration: 39.9s, size: 10.4 MB, start date/time: Nov 20, 2017 13:27:25.50
  2. env3_test_03_2.bag: duration: 39.1s, size: 10.2 MB, start date/time: Nov 20, 2017 13:28:56.41
  3. env3_test_03_3.bag: duration: 40.5s, size: 10.5 MB, start date/time: Nov 20, 2017 13:30:04.94
  • Scenario 04 (4 files):
  1. env3_test_04_1.bag: duration: 58.3s, size: 15.0 MB, start date/time: Nov 25, 2017 10:39:52.62
  2. env3_test_04_2.bag: duration: 57.2s, size: 14.7 MB, start date/time: Nov 25, 2017 10:41:16.31
  3. env3_test_04_3.bag: duration: 50.5s, size: 13.0 MB, start date/time: Nov 25, 2017 10:42:44.95
  4. env3_test_04_4.bag: duration: 1:01s, size: 15.7 MB, start date/time: Nov 25, 2017 10:43:52.44
  • Scenario 05 (1 file):
  1. env3_test_05.bag: duration: 15:15s, size: 236.8 MB, start date/time: Nov 26, 2017 11:33:13.31
  • Scenario 06 (1 file):
  1. env3_test_06.bag: duration: 09:18s, size: 143.3 MB, start date/time: Nov 26, 2017 12:25:45.12
  • Scenario 07 (1 file):
  1. env3_test_07.bag: duration: 4:16s, size: 65.1 MB, start date/time: Nov 25, 2017 11:40:01.65
  • Scenario 08 (1 file):
  1. env3_test_08.bag: duration: 03:39s, size: 55.8 MB, start date/time: Nov 25, 2017 12:25:29.22
  • Scenario 09 (5 files):
  1. env3_test_09_1.bag: duration: 22.9s, size: 6.1 MB, start date/time: Nov 25, 2017 10:50:02.95
  2. env3_test_09_2.bag: duration: 20.8s, size: 5.6 MB, start date/time: Nov 25, 2017 10:51:02.62
  3. env3_test_09_3.bag: duration: 34.3s, size: 9.0 MB, start date/time: Nov 25, 2017 10:51:45.96
  4. env3_test_09_4.bag: duration: 29.3s, size: 7.9 MB, start date/time: Nov 25, 2017 10:52:51.24
  5. env3_test_09_5.bag: duration: 36.9s, size: 9.7 MB, start date/time: Nov 25, 2017 10:54:00.13
  • Scenario 10 (1 file):
  1. env3_test_10.bag: duration: 15:50s, size: 240.5 MB, start date/time: Nov 20, 2017 13:07:40.16
  • Scenario 11 (1 file):
  1. env3_test_11.bag: duration: 03:50s, size: 58.7 MB, start date/time: Nov 25, 2017 11:48:33.90
  • Scenario 12 (3 files):
  1. env3_test_12_1.bag: duration: 43.6s, size: 11.3 MB, start date/time: Nov 20, 2017 13:33:23.74
  2. env3_test_12_2.bag: duration: 44.3s, size: 11.5 MB, start date/time: Nov 20, 2017 13:34:24.95
  3. env3_test_12_3.bag: duration: 37.3s, size: 9.7 MB, start date/time: Nov 20, 2017 13:35:31.55
  • Scenario 13 (3 files):
  1. env3_test_13_1.bag: duration: 57.8s, size: 14.9 MB, start date/time: Nov 25, 2017 11:01:15.23
  2. env3_test_13_2.bag: duration: 59.9s, size: 15.4 MB, start date/time: Nov 25, 2017 11:02:37.85
  3. env3_test_13_3.bag: duration: 54.0s, size: 13.9 MB, start date/time: Nov 25, 2017 11:04:30.69
  • Scenario 14 (1 file):
  1. env3_test_14.bag: duration: 05.57s, size: 90.5 MB, start date/time: Nov 25, 2017 11:10:32.97
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