International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 07 | July 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 864 Development and Design of Autonomous Navigation Robot Using Raspberry Pi and Computer Vision Dhruv Patel 1 , Priyam Dalwadi 2 , Shubham Dhumal 3 , Abhishek Bhalodiya 4 1-4 U.G. Student Mechatronics Engineering, ITM Vocational University - Vadodara, Gujarat, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Visual perception is the most important ability for any robot, animal or social animal to learn, process and act accordingly. Our paper represents the computer vision-based approach programmed in python language - using various libraries like OpenCV and NumPy on Raspberry Pi 3 model b+ to navigate robot autonomously. The high definition USB camera mounted on a custom-built chassis (.approx. 23 X 20 cm) captures the surrounding at several field rates. An algorithm based on simple geometric shape, area and color detection is developed to control the behavior of wheels. Digital image processing techniques like image thresholding and contours detection are used. The robot will operate autonomously without any manual control, it will act only on the data input from the camera, processed by the mini- computer as per the program written in it. Our experiment illustrates the efficacy of technology to gain results with least error. Key Words: Computer Vision, Digital Image Processing, Algorithm, Raspberry-Pi 3 model b+, Robot. 1. INTRODUCTION Human exposure to an unsafe work environment and recent COVID-19 pandemic has boosted the need to develop a technological solution. Small steps can be taken to reduce this vulnerability. 'Computer Vision' refers to the human visual like the tendency for a computer such as extracting, classifying and creating a model to act effectively. Lawrence Roberts (PhD at MIT, the Year 1963) is known as "Father of Computer Vision". "Machine Perception of Three-Dimensional Solids" is his most admired work. Robots are multipurpose programmable, versatile manipulators forged to locomote material, parts, tools, or specialized devices through various prearrange motions for the execution of a variety of assignments. The cyber-physical augmentation of computer vision on the robot or machine to perform a task is known as robot vision. Some work related to autonomous navigation has been done previously. Unlike other computer vision-based autonomous navigation techniques, to ease the process of way-finding use of simple geometric shapes of a specific colour and area calculation has been involved in this paper. This concept will navigate the robot more effectively. It will transform and advance more research based on driverless vehicle technology. The prototype involves a USB camera mounted on the front portion of a custom-built Acrylic robot chassis, Raspberry-pi 4 as robot brain, jumper wire as nerves to carry electric impulse, 12V DC geared motor as Actuator, Li- po battery. The USB camera will transmit the robot's view to Raspberry-Pi 3 model b+. The brain of the robot Raspberry- Pi processes raw input video using computer vision technique. OpenCV is a computer vision library used to perform digital image processing to control the vehicle in a smarter and intelligent way. The output generated during the various processes in raspberry-pi controls the behaviour of the robot by generating signals in the form of pulses to the motor driver circuit for wheel movement. Thus a complete system is established. Such types of an autonomous robot come to aid in a hazardous/non-hazardous environment to explore, deliver material or to carry operations by adding more functionality to it. 2. SOFTWARE IMPLEMENTATION A. Modus Operandi The environment which is captured using HD usb camera acts as input for raspberry pi. It is further processed by the algorithm based on the computer vision tool. The algorithm enhances geometric shapes that produce commands to perform the operation by the robot using a motor driver such as moving forward, stopping; turning left and right of the wheels. Computer vision techniques help us to understand more of image information, mainly the area of contour and counting edges of geometric shapes.