Autonomous guided vehicles (AGVs) are an important means of making transportation, logistics, and intra-logistics more environmentally friendly. Navigation and accident avoidance are perhaps the two most important features that still have plenty of opportunities for improvement. Technologies such as GPS, sonar, radar, and LIDAR have been successfully used and combined for this effect. More recently, image processing with multiple cameras has enabled the 3D reconstruction of the vehicle’s environment, at the expense of requiring state-of-the-art graphics processors. This chapter evaluates the viability of indoor navigation using a single camera and ArUco markers placed at known locations within the navigating environment when a global positioning system (GPS) is unavailable. If the location of external objects cannot be determined with a single camera, sonars can be used for collision avoidance. A custom-built AGV with differential steering and a simple universal serial bus (USB) webcam connected to a Raspberry Pi that processes the image to locate the robot in space are utilized. In addition, the Raspberry Pi transmits reference positions to an Arduino, which runs a proportional-integral-derivative (PID) control loop for each wheel of the AGV. The entire assembly is shown to locate, align, approach, and dock at docking stations. To compare with the calculated values, the effective position in relation to the markers is manually measured. With sufficient illumination and a clear path to the markers, it is shown that location calculation with a single camera and ArUco markers is precise enough for indoor navigation.


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    Titel :

    Indoor Navigation of an Autonomous Guided Vehicle Using ArUco Markers


    Weitere Titelangaben:

    Spri. Proceed. in Earth, Environ. Sci.


    Beteiligte:

    Kongress:

    International conference on Multidimensional Sustainability: Transitions and Convergences ; 2022 ; Vila Nova de Gaia, Portugal September 29, 2022 - September 30, 2022



    Erscheinungsdatum :

    07.12.2023


    Format / Umfang :

    21 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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