RT info:eu-repo/semantics/article
T1 People Detection and Tracking Using LIDAR Sensors
A1 Álvarez Aparicio, Claudia
A1 Guerrero Higueras, Ángel Manuel
A1 Rodríguez Lera, Francisco Javier
A1 Ginés Clavero, Jonatan
A1 Martín Rico, Francisco
A1 Matellán Olivera, Vicente
A2 Arquitectura y Tecnologia de Computadores
K1 Cibernética
K1 LIDAR
K1 Convolutional networks
K1 People tracking
K1 @home
K1 Robotic competitions
K1 1207.03 Cibernética
AB [EN] 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.
PB MDPI
LK https://hdl.handle.net/10612/18199
UL https://hdl.handle.net/10612/18199
NO Álvarez-Aparicio, C., Guerrero-Higueras, Á. M., Rodríguez-Lera, F. J., Clavero, J. G., Rico, F. M., and Matellán, V. (2019). People detection and tracking using LIDAR sensors. Robotics, 8(3). https://doi.org/10.3390/ROBOTICS8030075
NO Special Issue Robotics in Spain 2019
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 10-jun-2024