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People Detection and Tracking Using LIDAR Sensors

Supercomputación Castilla y León (SCAyLE), Campus de Vegazana s/n, 24071 León, Spain
Department Mechanical, Computer Science and Aerospace Engineering, University of León, Campus de Vegazana s/n, 24071 León, Spain
Department Telematics and Computing (GSyC), Universidad Rey Juan Carlos, Campus de Fuenlabrada, Camino del Molino s/n, 28943 Fuenlabrada, Spain
Author to whom correspondence should be addressed.
Robotics 2019, 8(3), 75;
Received: 15 July 2019 / Revised: 7 August 2019 / Accepted: 28 August 2019 / Published: 31 August 2019
(This article belongs to the Special Issue Robotics in Spain 2019)
The tracking of people is an indispensable capacity in almost any robotic application. A relevant case is the @home robotic competitions, where the service robots have to demonstrate that they possess certain skills that allow them to interact with the environment and the people who occupy it; for example, receiving the people who knock at the door and attending them as appropriate. Many of these skills are based on the ability to detect and track a person. It is a challenging problem, particularly when implemented using low-definition sensors, such as Laser Imaging Detection and Ranging (LIDAR) sensors, in environments where there are several people interacting. This work describes a solution based on a single LIDAR sensor to maintain a continuous identification of a person in time and space. The system described is based on the People Tracker package, aka PeTra, which uses a convolutional neural network to identify person legs in complex environments. A new feature has been included within the system to correlate over time the people location estimates by using a Kalman filter. To validate the solution, a set of experiments have been carried out in a test environment certified by the European Robotic League. View Full-Text
Keywords: LIDAR; convolutional networks; people tracking; @home; robotics competitions LIDAR; convolutional networks; people tracking; @home; robotics competitions
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MDPI and ACS Style

Álvarez-Aparicio, C.; Guerrero-Higueras, Á.M.; Rodríguez-Lera, F.J.; Ginés Clavero, J.; Martín Rico, F.; Matellán, V. People Detection and Tracking Using LIDAR Sensors. Robotics 2019, 8, 75.

AMA Style

Álvarez-Aparicio C, Guerrero-Higueras ÁM, Rodríguez-Lera FJ, Ginés Clavero J, Martín Rico F, Matellán V. People Detection and Tracking Using LIDAR Sensors. Robotics. 2019; 8(3):75.

Chicago/Turabian Style

Álvarez-Aparicio, Claudia, Ángel Manuel Guerrero-Higueras, Francisco Javier Rodríguez-Lera, Jonatan Ginés Clavero, Francisco Martín Rico, and Vicente Matellán. 2019. "People Detection and Tracking Using LIDAR Sensors" Robotics 8, no. 3: 75.

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