International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 05 | May 2024
p-ISSN: 2395-0072
www.irjet.net
Path Following Robot using Arduino and IR Sensors Om Rajkumar Solavat1 1K.J. Somaiya College of Engineering, Somaiya Vidyavihar University,
Mumbai, Maharashtra
2Professor Vaibhav Narwane, Dept. of Mechanical Engineering,
Somaiya Vidyavihar University, Mumbai, Maharashtra ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This project aims to design and fabricate a
Path-follower robots are used in industry to transport materials and objects autonomously by following a particular path, which may be drawn lines or magnetic tapes on the floor that are detected by a sensor array. High performance, high accuracy, lower labor cost, and the ability to work in hazardous places have put robotics in an important position over many other such technologies (6). In this paper path following robot has been presented which will trace a black path on a white surface with the help of IR Sensors, Arduino Board microcontroller, L298N Motor Driver, etc. AMRs follow the LSRB Algorithm, which is usually used in this type of robot. Therefore, this kind of Robot should sense the line with its Infrared Ray (IR) sensors installed under the robot. After that, the data is transmitted to the processor by specific transition buses. Hence, the processor is going to decide the proper commands and then it sends them to the driver and thus the path will be followed by the line follower robot.
mobile robot that can follow the path with the help of IR Sensors. Path following proves to be very useful in today’s modern technology and it is still considered an important field of robotics. This type of robot is based on decision-making algorithms. The main aim of this project is to make an Arduino-based efficient self-directed path-following robot. A simple path-following algorithm “LSRB algorithm” is used to make this robot. In this project, Hardware development, software development, and path construction have been done. For capability testing, the robot will implement to follow the black path and complete the maze. Key Words: Autonomous Mobile Robot, Arduino, LSRB Algorithm, Decision -making algorithm, Path Follower Robot, IR Sensor.
1. INTRODUCTION
Bhargav Srinivasan and S. Siva Sathya propose a genetic algorithm-based approach for maze solving using a mobile robot. Ajith Abraham and Crina Grosan propose a hybrid approach, which combines a genetic algorithm with a fuzzy logic controller to generate an optimal path through the maze. H.N. Krishnan and K.K. Gowtham (2018) built a robot whose movements are controlled by an Arduino microcontroller, which receives input from the image processing algorithm.
Path planning in Autonomous Mobile Robot Navigation is an important part of the robotics field. Autonomous Mobile Robots (AMRs) can be defined as robotic systems that are able to navigate without disruption and no human intervention in their movement, to avoid obstacles and follow a predefined path (1). The demand for AMRs is rising to its peak across various applications such as logistics transportation (2), robotic cleaning services (7), and surveillance for various purposes. This type of robot can also become a boon in the agriculture field if it is properly designed for unpredictable agricultural climates solving many problems for humans like labor shortages, natural phenomena, and economic issues (3).
1.1 Background of work In the middle of the 20th century, Path-following problems become an essential field of robotics. In the year of 1972, editors of IEEE Spectrum magazine came up with the concept of a micro-mouse which is a small microprocessorcontrolled vehicle with self-intelligence and capability to navigate a critical path. Then in May 1977, the fast US Micro mouse contest, called “Amazing Micro mouse Maze Contest” was announced by IEEE Spectrum. From then, this type of contest became more popular, and many types of mazesolving robots are developed every year. In the late 1970s, the designs of the path-solving robots’ designs were used to have huge physical shapes that contained many blocks of logic gates.
AMRs usually navigate through a globally defined geometric path with loose time constraints and can be divided into control theory-based methods and geometric methods (5). Control theory-based methods, such as Proportional– Integral–Derivative (PID) controllers, face challenges in finding optimal parameters (4). Geometric methods, compared to control theory-based methods, have become more popular due to their simplicity, robustness, and suitability for real-time control. The Pure Pursuit (PP) controller, proposed as the earliest geometric approach for path following, fits a circle through the vehicle’s current position to a point on the path ahead of the vehicle by a lookahead distance (5).
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