Processing of LiDAR and IMU data for target detection and odometry of a mobile robot

• Autorzy: Giannoccaro Nicola Ivan , Nishida Takeshi , Lay-Ekuakille Aimé , Velazquez Ramiro , Visconti Paolo

Identyfikatory

DOI

10.14313/JAMRIS/1-2022/1

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

mechatronic device; LiDAR sensor; measurement processing; 3D object recognition; robotic implementation

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2022
• Tom: Vol. 16, No. 1
• Strony: 3--13
• Opis fizyczny: Bibliogr. 30 poz., rys.

Twórcy

autor

Giannoccaro Nicola Ivan

• Department of Innovation Engineering, University of Salento, Lecce, 73100, Italy

autor

Nishida Takeshi

• Department of Control Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

autor

Lay-Ekuakille Aimé

• Department of Innovation Engineering, University of Salento, Lecce, 73100, Italy

autor

Velazquez Ramiro

• Universidad Panamericana, Aguascalientes, Ags, 20290, MEXICO

autor

Visconti Paolo

• Department of Innovation Engineering, University of Salento, Lecce, 73100, Italy

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).