Efficient Obstacle Avoidance and Target Tracking in Mobile Robots using Advanced Technique *

Abstract

Our study focuses on the design and implementation of an autonomous mobile robot, combining advanced computer vision techniques with a microprocessor for enhanced navigation capabilities. The primary objective is to develop a self-navigating robot that seamlessly moves from a starting point to a target while employing real-time obstacle avoidance and dynamic decision-making. By continuously scanning its environment using computer vision, the robot detects and adjusts its trajectory to avoid obstacles. Embedded algorithms enable precise obstacle identification, ensuring safe and collision-free navigation. Upon reaching the target, the robot autonomously halts. If the target is hidden, the robot explores its surroundings; if the target remains undetected, it signals its inability to achieve the goal. Powered by a Raspberry Pi, this system offers a robust and cost-effective solution for mobile robot navigation. The integration of advanced computer vision and obstacle avoidance significantly enhances the robot's operational capabilities, enabling effective navigation and target pursuit in complex environments.