To Design and Fabricate an Automated Guided Vehicle (Electronics and Control)

Ooi, Vei Cheik (2017) To Design and Fabricate an Automated Guided Vehicle (Electronics and Control). Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

This project aims to fabricate an Automated Guided Vehicle (AGV) that is able to locate and navigate itself to the desired destination using image processing technology integrated with auto localization and navigation algorithms. Raspberry Pi microcontroller was utilised as the central control of the AGV which it would process the information captured from the camera to make its navigation and localization decisions in real time. The communication between I/O devices and Raspberry Pi was established via the MQTT protocol which it operates as the medium for information exchange between the AGV and the user. OpenCV library was employed to process the images captured and generate outputs data to Raspberry Pi with the written algorithms. The prototype of storage racks with 3 rows, 3 column and 2 levels is built with navigation line on the floor to test the navigation and localisation performance of the AGV. The navigation and localisation of the AGV are based on the identification of the coloured tapes on the racks detected by the Pi Cam. The results of the project show that the AGV is able to locate itself at the determined destination and able to navigate based on the colour pathway to pick up or place materials to the designated racks accurately in the tolerance of ±3cm in all three directions namely x, y and z axes. The algorithm for the AGV to find the shortest path travel to its planned destinations was written with some case models to demonstrate its workability. The demonstration was tested in the dimensions of 3 (row) and 3 (column) only without the 2 (level) dimensions. During the demonstration, the errors in the algorithm were noted and amended for improvement. The limitations of this project are: First, the performance of the AGV in actual movement to find the shortest path could not be carried out due to the positions of the color tape to give signal to the AGV to stop at the rack stopping points were located with some offset in distance (for the AGV to stop). The offset was set in one direction only hence if the AGV coming from the other direction, it would miss the stopping point. Second, the AGV performance is very dependent on the strength of the WIFI signal. The signal of WIFI would affect the colour transmission and the time interval of frames captured by Pi Cam. These problems would hence affect the motion control and navigation performance of the AGV. As an industrial implication, this project could provide the industries an insight to fully automate the material handling operations in a warehouse using Raspberry Pi microcontroller and Pi Cam integrated with the localization and navigation algorithms.