Design and Implementation of an Self-navigating Transportation Robot: A Visual Image Recognition-Based Approach

Robots of various kinds are widely used to enhance production efficiency, alleviate the burden of manual labor, and bring innovation and progress to various fields. The importance of transportation robots lies in their ability to automatically execute cargo handling tasks, improving logistics efficiency, reducing human errors, lowering costs, and enhancing work environments. Transportation robots need to achieve core functions of motion control and object recognition. This study is dedicated to providing a low-cost, flexible, and efficient design and implementation of a multi-functional transport robot, requiring capabilities such as line tracking, positioning, recognition, grasping, and placing objects. To this end, the research proposes corresponding design and implementation frameworks, solutions for motion control and object recognition, and provides software and hardware design schemes. The study has completed the construction of the robot, conducted kinematic modeling, and subsequently proposed a series of control strategies and performance tuning methods. By incrementally debugging each function and conducting comprehensive system testing, the research results indicate that the robot successfully achieves all specified functions. The robot also maintains design redundancy and peripheral interfaces, enabling further upgrades and improvements tailored to specific application environments.