Design of a ROS-Based Vision-Guided Mobile Robot for Object Transportation

Abstract

With the advancement of industrial automation and smart logistics, there is growing demand for intelligent material handling solutions. This paper presents a ROS-based vision-guided mobile robot designed for autonomous navigation, object recognition, and grasping in complex environments. The system integrates a mobile chassis, robotic arm, and visual sensors, with optimized mechanical design for stability and mobility. Using ROS as the software framework, it implements SLAM-based navigation, computer vision for object detection, and motion planning for precise grasping. Experimental results demonstrate high navigation accuracy, reliable object recognition, and efficient grasping performance across various scenarios. The solution effectively addresses key challenges in smart logistics and automated production, showing significant potential for industrial applications. The integrated approach combining robust hardware design with advanced perception and control algorithms represents a practical advancement in autonomous material handling technology.