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

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

An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism

Recently, there has been increasing attention paid to AGV (Automated Guided Vehicle) in factories and warehouses to enhance the level of automation. In order to improve productivity, it is necessary to increase the efficiency of the AGV, including working speed and accuracy. This study presents a fuzzy-PID controller for improving the efficiency of a line-following AGV. A line-following AGV suffers from tracking errors, especially on curved paths, which causes a delay in the lap time. The fuzzy-PID controller in this study mimics the principle of human vehicle control as the situation-aware speed adjustment on curved paths. Consequently, it is possible to reduce the tracking error of AGV and improve its speed. Experimental results show that the Fuzzy-PID controller outperforms the PID controller in both accuracy and speed, especially the lap time of a line-following AGV is enhanced up to 28.6% with the proposed fuzzy-PID controller compared to that with the PID controller only

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

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

A Particle Swarm Optimization tuned nonlinear PID controller with improved performance and robustness for First Order Plus Time Delay systems

The Proportional, Integral, and Derivative (PID) controller is a ubiquitous controller within industry. The conventional PID controller can struggle to provide a satisfactory response for the nonlinear systems faced by industry. In addition, conventional PID controllers have a trade-off between performance and robustness, where they cannot compensate for both without compromising stability or speed. In this paper, a novel Nonlinear gains Proportional, Integral, and Derivative (NLPID) control algorithm is proposed as a practical control strategy that shows improvements in the simultaneous set-point tracking and disturbance rejection, to control nonlinear systems. The paper shows the performance and robustness of the proposed controller for the case of a First Order Plus Time Delay (FOPTD) system, which heavily exists in industry. The Particle Swarm Optimization (PSO) algorithm is used to tune the proposed NLPID controller. The performance of the proposed NLPID controller is simulated and compared against established controllers in literature such as conventional PID, two degree of freedom PID, and Smith Predictor PID controllers in MATLAB/Simulink for an FOPTD system, with various uncertainties and disturbances. This study shows that the proposed NLPID controller maintains faster settling and rise time, with no overshoot and excellent disturbance rejection, without compromising stability or speed, and is robust against parametric, additive, and multiplicative uncertainties

Mobile robot control and guidance using computer vision

Teória riadenia je aplikovaná takmer všade okolo nás, počnúc reguláciou teploty v našich domoch cez modelovanie správania sa trhu až po riadenie vesmírnych lodí. Dôvod, prečo je tomu tak je, je jej výkonnosť a krása, obe skryté v použitých matematických aparátoch. Kolesové mobilné roboty sú taktiež veľmi rozšírené, hlavne v priemysle, kvôli ich obrovskej nosnosti, ktorá je nevyhnutná. Veľmi presné detekovanie trasy je dôležité kvôli dôslednému riadeniu robota po jeho ceste. Jedna z najjednoduchších možností ako vynačiť trasu je použitie čiary, ktorá má iné optické vlastnosti ako jej podklad. Na detekovanie takto určenej trasy existuje niekoľko metód, ale najvýkonnejšie a najefektívnejšie je použitie kamery s následným digitánym spacovaním obrazu, ktoré je síce náročné na výpočtovú silu, ale je ním možne získať obrovské množstvo dát. Hoci táto metóda môže vyzerať zastaralo (vodiaca čiara) stále sa využíva v niektorých projektoch práve kvôli jej jednoduchosti a nízkej cene. Skutočné použitie kamery pre navigáciu všeobecne (nie pomocou čiary) je dokonca zatiaľ oblasť, ktorá je stále vo vývoji. Cieľom tejto práce je zostaviť malý mobilný robot, vytvoriť matematický model, navrhnúť niekoľko regulátorov a riadiť robot po vyznačenej čiare za použitia camery a počítačového videnia.Products of theory of control are almost everywhere around us beginning with temperature controller in our houses through modeling of market behavior to spaceship control. The reason of its widespread is its performance and beauty hidden in mathematical approach. Wheeled mobile robots are also widely used in industry because of their loading capability which is necessary. High accuracy path-tracking is very important for the mobile robots to precisely follow the designed path. One of the easiest way how to mark the path is to use line with different optical features than background. There are several methods to detect line and most powerful and efficient is camera usage. Subsequently, there is need to use digital image processing which demanding for computational performance but there is possibility to obtain huge amount of data. Although this principle could look obsolete (guide line) it is still used in many solutions because of its simplicity and cheapness. What is more, using camera to navigate robot global (without using line) is sort of modern technology and it is still in development. Objective of this work is to assembly small mobile robot, create its mathematical model, design several controllers and use camera and computer vision for robot guidance using guide line.