Machine learning and Sensor-Based Multi-Robot System with Voice Recognition for Assisting the Visually Impaired

Abstract

Navigating through an environment can be challenging for visually impaired individuals, especially when they are outdoors or in unfamiliar surroundings. In this research, we propose a multi-robot system equipped with sensors and machine learning algorithms to assist the visually impaired in navigating their surroundings with greater ease and independence. The robot is equipped with sensors, including Lidar, proximity sensors, and a Bluetooth transmitter and receiver, which enable it to sense the environment and deliver information to the user. The presence of obstacles can be detected by the robot, and the user is notified through a Bluetooth interface to their headset. The robot's machine learning algorithm is generated using Python code and is capable of processing the data collected by the sensors to make decisions about how to inform the user about their surroundings. A microcontroller is used to collect data from the sensors, and a Raspberry Pi is used to communicate the information to the system. The visually impaired user can receive instructions about their environment through a speaker, which enables them to navigate their surroundings with greater confidence and independence. Our research shows that a multi-robot system equipped with sensors and machine learning algorithms can assist visually impaired individuals in navigating their environment. The system delivers the user with real-time information about their surroundings, enabling them to make informed decisions about their movements. Additionally, the system can replace the need for a human assistant, providing greater independence and privacy for the visually impaired individual. The system can be improved further by incorporating additional sensors and refining the machine learning algorithms to enhance its functionality and usability. This technology has the possible to greatly advance the value of life for visually impaired individuals by increasing their independence and mobility. It has important implications for the design of future assistive technologies and robotics.