This paper presents the practical implementation of a computer vision algorithm designed for obstacle avoidance in a Robotino. The core of this implementation involves the development of a visual perception system leveraging the capabilities of Kinect V1 sensors. These sensors enable the acquisition of three-dimensional data about the Robotino's surroundings. From this wealth of visual information, an object detection and tracking algorithm has been meticulously crafted. This algorithm excels at identifying obstacles within the Robotino's path, a critical capability for navigating complex industrial environments. To ensure smooth and collision-free movement, an obstacle avoidance algorithm has been integrated. This obstacle avoidance strategy builds upon trajectory planning and motion control techniques, granting the Robotino the autonomy needed to maneuver adeptly and circumvent any detected obstacles. The significance of this research lies in its successful implementation of a comprehensive visual perception system and an advanced obstacle avoidance algorithm. These enhancements significantly elevate the autonomous mobility of robots within intricate industrial settings. The potential implications encompass heightened operational efficiency, enhanced safety, cost reduction, and shortened production cycles in the industrial processes.