DOI: 10.5281/zenodo.11504582
title: Multi-Domain Dataset for Robots (MDDRobots) - Multi-Domain Indoor Dataset for Visual Place Recognition and Anomaly Detection by Mobile Robots

description: The dataset is password-protected until the article is accepted by the Scientific Data Journal. After acceptance, the dataset will be available to everyone. For any questions, comments or other issues please contact Piotr Woźniak, email: p.wozniak@prz.edu.pl.

License

The MDDRobots dataset is made available under the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/.

Summary

The Multi-Domain Dataset for Robots (MDDRobots) contains data for computer vision problems, indoor place recognition, and anomaly detection. The recorded images are from different cameras and indoor environmental conditions. 

It is obligatory to cite the following paper in every work that uses the dataset: 

Wozniak, P.; Krzeszowski T.; Kwolek B.: Multi-Domain Dataset for Indoor Place Recognition and Anomaly Detection by Mobile Robots, Scientific Data, ISSN: 2052-4463, 2024.

Data description

The data is divided into five sets, each containing data for different cameras, which have further subsets. Each subset (Training, Test 1, Test 2, and Test 3) consists of nine sequences. There are a total of 87,750 three-channel RGB color images in PNG format organized into 19 zip folders. Each image in the sequence is labeled to represent a room. The number of images for each subset differs due to the division into training and testing data, as well as different methods of recording the sequences. To ensure a balanced dataset, each room in the sequence has the same number of images. Different environmental changes are introduced in each subset, mainly due to changes in the route, robot, and recording equipment. The rooms are well-lit but not overexposed. Test 1 data are closest to those from the training set. Test 3 sequences present changed conditions, such as a different time of day, a changed lighting system, and intensive equipment changes. Test 2 sequences pose the most significant challenge as they contain various recorded activities performed by people moving around rooms. This sequence data does not appear in the Xtion subset.

Dataset structure



RobotPiCamera_DataSet



DataSet_RobotPiCamera_RGB_train

DataSet_RobotPiCamera_RGB_test1

DataSet_RobotPiCamera_RGB_test2

DataSet_RobotPiCamera_RGB_test3



 Xtion_DataSet



DataSet_XTION_RGB_train

DataSet_XTION_RGB_test1

DataSet_XTION_RGB_test3



 GOPRO_DataSet



DataSet_GOPRO_RGB_train

DataSet_GOPRO_RGB_test1

DataSet_GOPRO_RGB_test2

DataSet_GOPRO_RGB_test3



iPhone_DataSet



DataSet_IPHONE_RGB_train

DataSet_IPHONE_RGB_test1

DataSet_IPHONE_RGB_test2

DataSet_IPHONE_RGB_test3



P40PRO_DataSet



DataSet_P40PRO_RGB_train

DataSet_P40PRO_RGB_test1

DataSet_P40PRO_RGB_test2

DataSet_P40PRO_RGB_test3




Example folder content: DataSet_P40PRO_RGB_train\Corridor1_RGB - 00000000.png, 00000001.png, 00000002.png, 00000003.png, ... 00000599.png.

Total Images (Images per Place)




Subset
Mounted
Training
Test 1
Test 2
Test 3


Pi Camera
Robot
7200 (800)
5400 (600)
5400 (600)
5400 (600)


Xtion
Robot
7200 (800) 
1800 (200) 
-
1800 (200) 


GoPro
Hand
5400 (600)
4500 (500)
4500 (500)
4500 (500)


iPhone
Hand
5400 (600) 
4500 (500)
4500 (500)
4500 (500) 


P40Pro
Hand
5400 (600)
4050 (450)
3150 (350) 
3150 (350) 




Further information

For any questions, comments or other issues please contact Piotr Woźniak <p.wozniak@prz.edu.pl>.