Line Follower Robot: Design and Hardware Application

Tayal, Satyam; Rao, Harsh Pallav Govind; Bhardwaj, Suryansh; Aggarwal, Harsh

doi:10.1109/icrito48877.2020.9197968

Cited by 15 publications

(7 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Robot merupakan mesin yang telah dirancang secara khusus untuk menyelesaikan berbagai macam tugas yang berdedikasi dan berulang secara cepat, presisi serta memiliki daya tahan. salah satunya perkambangan robot autonomous seperti robot line follower sering digunakan di industri sebagai pembawa barang, pembersih lantai, layanan pengiriman dan transportasi (Tayal, dkk, 2020). Robot Line follower adalah robot pengikut garis, biasanya mengikuti garis hitam dan putih.…”

Section: Pendahuluanunclassified

Optimasi Teknologi Computer Vision pada Robot Industri Sebagai Pemindah Objek Berdasarkan Warna

MASRIL¹,

CANIAGO²

2023

ELKOMIKA

View full text Add to dashboard Cite

ABSTRAKComputer vision merupakan teknologi yang dapat mendeteksi objek yang ada disekitarnya pada penelitian ini membahas optimasi teknologi computer vison pada robot sebagai pemindah objek berdasarkan warna. Sistem pada robot terdiri dari pengenalan bola berwarna dan memindahkan bola berwarna sesuai dengan warna yang dideteksi. Teknologi computer vision pada pixy 2 camera dapat mendeteksi objek berwarna menggunakan metode deteksi real-time dengan hasil optimasi yang tinggi yaitu 0,2 detik ketika mendeteksi objek berwarna. Pengujian pengenalan objek berwarna dilakukan sebanyak tiga kali pada setiap objek berwarna dengan tingkat akurasi sebesar 100%. Optimasi computer vision dapat membantu robot mengenali objek berwarna.Kata kunci: Computer Vision, Deteksi Objek Berwarna, Pixy2 Camera, Real-Time ABSTRACTComputer vision is a technology that can detect objects that are around it. This study discusses the optimization of computer vision technology on robots as object transfers based on color. The system on the robot consists of recognizing colored balls and moving colored balls according to the detected color. Computer vision technology on the pixy 2 camera can detect colored objects using a real-time detection method with a high optimization result of 0.2 seconds when detecting colored objects. The color object recognition test was carried out three times on each colored object with an accuracy rate of 100%. Computer vision optimization can help robots recognize colored objects.Keywords: Computer Vision, Color Object Detection, Pixy2 Camera, Real-Time

show abstract

Section: Pendahuluanunclassified

Optimasi Teknologi Computer Vision pada Robot Industri Sebagai Pemindah Objek Berdasarkan Warna

MASRIL¹,

CANIAGO²

2023

ELKOMIKA

View full text Add to dashboard Cite

show abstract

“…Robots are capable of doing tasks effectively and contributing to human lives. Mobile robots are often ones that can move from one location to another to do desired and challenging activities [8,9]. A mobile robot, for example, is employed in Urban Search and Rescue (USAR) to locate people and help rescue them in emergencies such as earthquakes or terrorist attacks.…”

Section: Introductionmentioning

confidence: 99%

Vision Navigation Based PID Control for Line Tracking Robot

Farkh¹,

Aljaloud²

2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

In a controlled indoor environment, line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots. A line tracking robot is a self-mobile machine that can recognize and track a painted line on the floor. In general, the path is set and can be visible, such as a black line on a white surface with high contrasting colors. The robot's path is marked by a distinct line or track, which the robot follows to move. Several scientific contributions from the disciplines of vision and control have been made to mobile robot vision-based navigation. Localization, automated map generation, autonomous navigation and path tracking is all becoming more frequent in vision applications. A visual navigation line tracking robot should detect the line with a camera using an image processing technique. The paper focuses on combining computer vision techniques with a proportional-integral-derivative (PID) controller for automatic steering and speed control. A prototype line tracking robot is used to evaluate the proposed control strategy.

show abstract

“…It also has low power and good performance [3]. DC motors have been widely applied in various applications, such as in mobile robots [4] [5][6] [7], mini conveyors [8], and electric vehicles [9].…”

Section: Introductionmentioning

confidence: 99%

Improved LQR Control Using PSO Optimization and Kalman Filter Estimator

et al. 2022

View full text Add to dashboard Cite

The electric motor is a device that converts electrical power into mechanical power. The DC motor has some advantages compared to the AC motor on its easier way to control the speed or position and wide adjustable range. The alternative solution for a control method with simple, easy to design, and can be implemented in a multi-input multi-output system is the integral state feedback such as LQR. The weakness of LQR control is that there is no exact method to determine the best value of matrix Q and R used to calculate the state feedback gain. Therefore, it was chosen by trial (manually tuned). This paper proposed an improved LQR control using PSO optimization and the Kalman filter estimator. The PSO is used to find optimal Q and R value while the Kalman filter is used to reduce the number of sensors used to measure the system state. Both performance and energy consumption were compared by using IAE and total energy consumption. The simulation results showed that the proposed method is superior in performance and energy compared to manually tuned LQR. The hardware implementation proves that the proposed method has the smallest IAE, whereas the smallest energy is manually tuned LQR. The proposed method can reduce the IAE by 11.28% with 1% higher energy compared to manually tuned LQR.

show abstract

Line Follower Robot: Design and Hardware Application

Cited by 15 publications

References 8 publications

Optimasi Teknologi Computer Vision pada Robot Industri Sebagai Pemindah Objek Berdasarkan Warna

Optimasi Teknologi Computer Vision pada Robot Industri Sebagai Pemindah Objek Berdasarkan Warna

Vision Navigation Based PID Control for Line Tracking Robot

Improved LQR Control Using PSO Optimization and Kalman Filter Estimator

Contact Info

Product

Resources

About