PDT - Pallets Detector and Tracker

What is PDT?

PDT is a public repository of codes and datasets for detecting and tracking the pallets in Warehouses based on machine learning approaches using a 2D Laser Rangefinder (LRF).

The proposed system for pallets detection and tracking is mainly composed of two main components:

1. a Faster Region-based Convolutional Network (Faster R-CNN) detector which is followed by CNN classifier for detecting the pallets.
2. a motion-based Kalman filter for tracking and increasing the confidence of the presence of the pallet.

Youtube Videos: PDT Youtube Video

Licensing and Citations

This dataset is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY, including the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. The authors allow the users of the Data Set to use and modify it for their own research. Any commercial application, redistribution, etc... has to be arranged between users and authors individually.

Eventually, if you use PDT or relevant to your academic work, please cite:

@article{mohamed2018detection,
title={Detection, localisation and tracking of pallets using machine learning techniques and 2D range data},
author={Mohamed, Ihab S. and Capitanelli, Alessio and Mastrogiovanni, Fulvio and Rovetta, Stefano and Zaccaria, Renato},
journal={Neural Computing and Applications},
year={2019}
}

@article{mohamed20182d,
title={A 2D laser rangefinder scans dataset of standard EUR pallets},
author={Mohamed, Ihab S and Capitanelli, Alessio and Mastrogiovanni, Fulvio and Rovetta, Stefano and Zaccaria, Renato},
journal={Data in Brief},
year={2019}
}

For further license information, please contact the authors.

Authors contacts

If you want to be informed about dataset updates and new code releases, obtain further information about the provided dataset, or contribute to its development please write to:

• Ihab S. Mohamed, dept. DIBRIS Università degli Studi di Genova (Italy), [email protected]
• Alessio Capitanelli, dept. DIBRIS Università degli Studi di Genova (Italy), [email protected]
• Fulvio Mastrogiovanni, dept. DIBRIS Università degli Studi di Genova (Italy), [email protected]
• Stefano Rovetta, dept. DIBRIS Università degli Studi di Genova (Italy), [email protected]
• Renato Zaccaria, dept. DIBRIS Università degli Studi di Genova (Italy), [email protected]