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

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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.
Twórcy
  • Department of Innovation Engineering, University of Salento, Lecce, 73100, Italy
  • Department of Control Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
  • Department of Innovation Engineering, University of Salento, Lecce, 73100, Italy
  • Universidad Panamericana, Aguascalientes, Ags, 20290, MEXICO
  • Department of Innovation Engineering, University of Salento, Lecce, 73100, Italy
Bibliografia
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  • [13] N. I. Giannoccaro, T. Nishida, “The Design, Fabrication and Preliminary Testing of a Variable Configuration Mobile Robot”, International Journal of Robotics and Automation Technology, 2019, 6, pp. 47–54.
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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).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c5899b4e-1175-46a4-8eca-0ce49ff87429
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