<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, the processing of the data of a 3D light detection and distance measurement (LiDAR) sensor mounted on a mobile robot is demonstrated, introducing an innovative methodology to manage the data and extract useful information. The LiDAR sensor is placed on a mobile robot which has a modular design that permits the easy change of the number of wheels, was designed to travel through several environments, and saves energy by changing the number and arrangement of the wheels in each environment. In addition, the robot can recognize landmarks in a structured environment by using a classification technique on each frame acquired by the LiDAR. Furthermore, considering the experimental tests, a new simple algorithm based on the LiDAR data processing together with the inertial data (IMU sensor) through a Kalman filter is proposed to characterize the robot’s pose by the surrounding environment with fixed landmarks. Finally, the limits of the proposed algorithm have been analyzed, highlighting new improvements in the future prospective development for permitting autonomous navigation and environment perception with a simple, modular, and low-cost device.</p>
</abstract>

In this paper, the processing of the data of a 3D light detection and distance measurement (LiDAR) sensor mounted on a mobile robot is demonstrated, introducing an innovative methodology to manage the data and extract useful information. The LiDAR sensor is placed on a mobile robot which has a modular design that permits the easy change of the number of wheels, was designed to travel through several environments, and saves energy by changing the number and arrangement of the wheels in each environment. In addition, the robot can recognize landmarks in a structured environment by using a classification technique on each frame acquired by the LiDAR. Furthermore, considering the experimental tests, a new simple algorithm based on the LiDAR data processing together with the inertial data (IMU sensor) through a Kalman filter is proposed to characterize the robot’s pose by the surrounding environment with fixed landmarks. Finally, the limits of the proposed algorithm have been analyzed, highlighting new improvements in the future prospective development for permitting autonomous navigation and environment perception with a simple, modular, and low-cost device.

Processing of LiDAR and IMU Data for Target Detection and Odometry of a Mobile Robot

Journal of Automation, Mobile Robotics and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

In this paper, the processing of the data of a 3D light detection and distance measurement (LiDAR) sensor mounted on a mobile robot is demonstrated,...

Processing of LiDAR and IMU Data for Target Detection and Odometry of a Mobile Robot

Pubblicato online: 04 apr 2023

Pagine: 3 - 13

Ricevuto: 10 giu 2021

Accettato: 02 ago 2022

DOI: https://doi.org/10.14313/jamris/1-2022/1

Parole chiave
mechatronics device, LiDAR sensor, measurement processing, 3D object recognition, robotic implementation

© 2022 Nicola Ivan Giannoccaro et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Processing of LiDAR and IMU Data for Target Detection and Odometry of a Mobile Robot

Pubblicato online: 04 apr 2023

Pagine: 3 - 13

Ricevuto: 10 giu 2021

Accettato: 02 ago 2022

DOI: https://doi.org/10.14313/jamris/1-2022/1

Parole chiavemechatronics device, LiDAR sensor, measurement processing, 3D object recognition, robotic implementation

© 2022 Nicola Ivan Giannoccaro et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
mechatronics device, LiDAR sensor, measurement processing, 3D object recognition, robotic implementation