Sistem Navigasi Automated Guided Vehicle Berbasis Computer Vision dan Implementasi pada Raspberry Pi

Setiawan, Florentinus Budi; Wijaya, Oei Jevon Aldo; Pratomo, Leonardus Heru; Riyadi, Slamet

doi:10.17529/jre.v17i1.18087

Cited by 10 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Setiawan et al have developed a robot for delivering goods based on an automated guided vehicle. He set the motion of the robot, then controlled it through computer vision, and then used the camera as a sensor to determine the current path in the form of instructions using the navigation system [ 3 ]. Weng et al proposed an improved model with a state classification model and a smooth transition strategy to solve the problems of actuator saturation, parameter selection, and bias relationship of the automated guided vehicle controller [ 4 ].…”

Section: Related Workmentioning

confidence: 99%

Path Planning and Trajectory Tracking for Automatic Guided Vehicles

Tang

Zhou

Hao

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Automated guided vehicle technology has become a hot area of scientific research due to its increasing use in manufacturing and logistics. Its main features are programming and control, remote computer eye tracking, command receiving and execution, autonomous route planning, and autonomous driving execution of tasks, with the advantages of high intelligence and flexibility. In this work, a simple vehicle model is used to study the route planning and tracking control of automatic guided vehicles. This paper uses wireless communication to find the optimal route planning problem. Using geometric methods, we develop a model of the working environment of the mobile automatic guided vehicle and develop a route finding algorithm. Based on the kinematic model, an advanced routing controller is designed to conduct experimental simulation of two trajectories and verify the effectiveness of the trajectory tracking controller. When the time is after 2 s, the position error is almost completely zero. In the path planning, when the number of iterations is greater than 10, the path length remains constant, verifying the effectiveness of the method in this paper.

show abstract

Section: Related Workmentioning

confidence: 99%

Path Planning and Trajectory Tracking for Automatic Guided Vehicles

Tang

Zhou

Hao

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Untuk mencapai hasil terbaik, diperlukan perencanaan yang cermat dengan mempertimbangkan sifat dan karakteristik masing-masing komponen yang digunakan. Hal ini bertujuan untuk mencegah terjadinya kerusakan pada komponen-komponen tersebut [9]. tahap perancangan melibatkan beberapa langkah, mulai dari perancangan blok diagram hingga mencapai perancangan keseluruhan alat.…”

Section: Metodologiunclassified

Implementasi Smart Home pada Platform Apple Homekit dan Google Home dengan Raspberry Pi 4B

Robbani,

Alfiaturrohmah,

Nurdiansyah

et al. 2024

jtim

View full text Add to dashboard Cite

This research examines the significant impact of technological advances, especially in the Internet of Things (IoT) paradigm, on various aspects of human life strongly manifested during the In-dustrial Revolution Era 4.0. The main focus of this research is on the application of advanced and innovative IoT concepts in the context of smart homes, integrating popular platforms such as Apple HomeKit and Google Home. The temperature sensor (DHT11) and light sensor (LDR) play a key role as important input elements, enabling the optimization of smart home automation functions. Raspberry Pi 4B was chosen as the main platform, the "brain" of the system, providing reliable computing capabilities. Using four-channel relays, this research specifically aims to increase ef-ficiency and integration in controlling devices in the smart home ecosystem. By emphasizing the concept of optimization, this research proposes a smart solution that is expected to not only provide an integrated and efficient experience for smart home users but also unlock the potential for further development of IoT technology. As a result, the implementation of the solutions proposed in this research is expected to create a smart home that is not only technologically smart but also responsive to the needs and preferences of its occupants, paving the way for further in-novation in the development and application of the Internet of Things in various contexts of human life.

show abstract

“…The Raspberry Pi's clock is much larger than those of competing microcontrollers, and its RAM is significantly more advanced than that of most other microcontrollers; in short, it has features more commonly associated with computers B. Setiawan, O. J. Aldo Wijaya, L. H. Pratomo, and S. Riyadi (2021). Computers the size of a microwave running the Python programming language and the OpenCV library are used in the development of this AGV robot; the library makes use of OCR, or optical character recognition, developed by Draganjac.I & Bogdan.…”

Section: Introductionmentioning

confidence: 99%

Pattern Recognition on Automated Guided Vehicles Two Wheel Drive (AGV 2WD) Robot for Location Detection Based on Raspberry Pi 4 Model B

Setiawan

Muntaha

Pratomo

et al. 2023

SinkrOn

View full text Add to dashboard Cite

AGV (Automated Guided Vehicle) equipped with artificial intelligence (AI) is anticipated to boost Indonesia's industrial development. The little computer used to generate this robot's artificial intelligence used mechanical gears similar to those found in an eight-wheeled, two-wheel-drive car (2WD). This article outlines and demonstrates the usage of an AGV-controlled approach to determine a place inside a building by detecting text in different locations throughout the building. The current technique employs the programming languages Python and OpenCV. Optical Character Recognition (OCR) has been tweaked or enhanced for usage with OpenCV. Multiple texts are read using OCR as the principal technique. In this instance, OCR functions at many stages of the process, in addition to being employed for exploring letters and words, word translation, character classification, linguistic analysis, and adaptive character classification. The output text from the system's document processing procedure will likely contain the location or even the position of an AGV robot once the process has concluded. This text is produced from the text that was previously submitted using the camera function. After a thorough search, the AGV robot will go to the next area before returning to its starting point. The method above can be implemented on the AGV lab's hardware, which has a solid basis

show abstract

Sistem Navigasi Automated Guided Vehicle Berbasis Computer Vision dan Implementasi pada Raspberry Pi

Cited by 10 publications

References 8 publications

Path Planning and Trajectory Tracking for Automatic Guided Vehicles

Path Planning and Trajectory Tracking for Automatic Guided Vehicles

Implementasi Smart Home pada Platform Apple Homekit dan Google Home dengan Raspberry Pi 4B

Pattern Recognition on Automated Guided Vehicles Two Wheel Drive (AGV 2WD) Robot for Location Detection Based on Raspberry Pi 4 Model B

Contact Info

Product

Resources

About