PID control applied on a line-follower AGV using a RGB camera

Gomes, Mariana; Bassora, L.A; Morandin, Orides; Vivaldini, Kelen Cristiane Teixeira

doi:10.1109/itsc.2016.7795553

Cited by 22 publications

(9 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Gomes et al developed a control algorithm for AGV model to follow the predefined path by line avoiding oscillation on its movement. Cameras were used inside PID control loop to track path [25]. Kim et al [26] have designed the obstacle avoidance system for AGV by using fuzzy logic control with PID control.…”

Section: Proportional Integral Derivative (Pid)mentioning

confidence: 99%

“…It is a recursive procedure, which breaks the design problem of controller into sub design problems and progressively stabilizes sub design system. It requires less computational time and converges fast with less disturbance in nonlinear system, but the algorithm robustness is not efficient [25]. While, Partama et al have proposed a trajectory tracking algorithm for AGV system using backstepping controller unknown wheel radii.…”

Section: Backstepping Controllermentioning

confidence: 99%

See 1 more Smart Citation

A Review of Control Algorithm for Autonomous Guided Vehicle

Gul

2020

IJEECS

View full text Add to dashboard Cite

The autonomous guided vehicle is a efficient and effective platform for control system. Their non-linear nature helps in analysing the control algorithms more efficiently and effectively. The main objective of path planning is to find the optimal and shortest path avoiding the time complexity so environment can be modelled completely for vehicle. The paper includes explanation of different systems together with numerous algorithms have been discussed with advantages and disadvantages for example: Fuzzy control, Neural Control, Back-stepping control, Adaptive control, Sliding mode control and PID control and linear quadratic regulator. The conclusion includes the hybrid system integration based on the advantages and disadvantages presented in this paper.

show abstract

Section: Proportional Integral Derivative (Pid)mentioning

confidence: 99%

Section: Backstepping Controllermentioning

confidence: 99%

A Review of Control Algorithm for Autonomous Guided Vehicle

Gul

2020

IJEECS

View full text Add to dashboard Cite

show abstract

“…Sensor bekerja dengan menangkap data pantulan cahaya infrared yang dipancarkan ke garis berwarna hitam yang kemudian di olah dengan algoitma tertentu agar robot dapat menuju lokasi pengambilan atau pun penyimpanan barang di gudang yang diinginkan oleh pengguna. Beberapa penelitian juga telah menggunakan sebuah kamera sebagai pengganti sensor optik infrared karena kemudahan pemasangan dan integrasi dengan perangkat lain (Gomes et al, 2016). Untuk model yang cukup lama digunakan adalah model magnetic dengan keunggulan tidak dipengaruhi oleh cahaya namun dari memiliki kesulitan dari segi pemasangan insfrastuktur pendukungnya yaitu lintasan magnetic yang dibangun (Qi, Zhou and Yang, 2016).…”

Section: Pendahuluanunclassified

Desain dan Simulasi Sistem Kendali PID Pada AGV(Automated Guided Vehicle) Pengikut Garis

Riansyah¹

2019

Journal Of Information Technology

View full text Add to dashboard Cite

Abstrak. Efektivitas dan efisiensi di bidang Logistik menjadi hal yang sangat penting. Salah satu solusi yang dilakukan untuk meningkatkan hal tersebut adalah bagaimana mengotomasi proses logistik dengan teknologi robotika yang disebut dengan AGV (Automated Guide Vehicle). Pada penelitian ini akan dikembangkan AGV yang dikendalikan dengan suatu algoritma agar dapat mengikuti lintasan berupa garis berwarna putih pada saat bertugas memindahkan material dari satu tempat ke tempat lain di dalam proses logistik. Sistem kendali yang digunakan adalah kendali PID (Proportional, Integral, Derivative), dengan dukungan perangkat keras berupa kamera RGB-D sebagai alat navigasi AGV untuk mendeteksi dan mengikuti lintasan. Sistem Kendali PID berfungsi untuk menjaga agar AGV tetap berada pada lintasan yang dibuat. Pengujian dilakukan dengan membandingkan nilai-nilai parameter baik kendali P, PD, dan PID agar mendapatkan parameter yang menghasilkan respon paling baik sehingga AGV mampu bergerak mengikuti lintasan garis berwarna putih. AGV telah dirancang dan disimulasikan dalam sebuah perangkat lunak open source yang dikenal sebagai simulator Gazebo dan ROS (Robot Operating System). Proses navigasi menggunakan algoritma deteksi garis dengan tahapan melakukan filtering dan thresholding untuk menentukan titik pusat moment gambar lintasan garis putih. Dengan adanya titik pusat tersebut, AGV bergerak mengikuti pola lintasan dengan membandingkannya terhadap titik referensi yang telah ditentukanKata Kunci: Kendali PID, AGV (Automated Guided Vehicle), RGB-D, Simulator Gazebo, ROS(Robot Operating System)

show abstract

“…Meanwhile, other research applied a PID control algorithm to adjust the robot on the line. In [8] - [9], the line follower robot was equipped with a webcam mounted on the vehicle and connected to Matlab platform.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Computer Vision Based Line Followers Using Raspberry Pi and Jetson Nano

Dewantoro

Mansuri

Setiaji

2021

JRE

View full text Add to dashboard Cite

The line follower robot is a mobile robot which can navigate and traverse to another place by following a trajectory which is generally in the form of black or white lines. This robot can also assist human in carrying out transportation and industrial automation. However, this robot also has several challenges with regard to the calibration issue, incompatibility on wavy surfaces, and also the light sensor placement due to the line width variation. Robot vision utilizes image processing and computer vision technology for recognizing objects and controlling the robot motion. This study discusses the implementation of vision based line follower robot using a camera as the only sensor used to capture objects. A comparison of robot performance employing different CPU controllers, namely Raspberry Pi and Jetson Nano, is made. The image processing uses an edge detection method which detect the border to discriminate two image areas and mark different parts. This method aims to enable the robot to control its motion based on the object captured by the webcam. The results show that the accuracies of the robot employing the Raspberry Pi and Jetson Nano are 96% and 98%, respectively.

show abstract

PID control applied on a line-follower AGV using a RGB camera

Cited by 22 publications

References 1 publication

A Review of Control Algorithm for Autonomous Guided Vehicle

A Review of Control Algorithm for Autonomous Guided Vehicle

Desain dan Simulasi Sistem Kendali PID Pada AGV(Automated Guided Vehicle) Pengikut Garis

Comparative Study of Computer Vision Based Line Followers Using Raspberry Pi and Jetson Nano

Contact Info

Product

Resources

About