Development of a Robotic System for Automatic Wheel Removal and Fitting
This addresses the problem of spinal/muscular injuries and safety risks during manual tire changing for automotive technicians, though it appears incremental in applying existing algorithms to this specific task.
This paper developed image processing and computer vision algorithms for real-time detection and tracking of vehicle wheels to enable a robotic system for automatic tire changing, aiming to make the process faster, safer, and more efficient.
This paper discusses the image processing and computer vision algorithms for real time detection and tracking of a sample wheel of a vehicle. During the manual tyre changing process, spinal and other muscular injuries are common and even more serious injuries have been recorded when occasionally, tyres fail (burst) during this process. It, therefore, follows that the introduction of a robotic system to take over this process would be a welcome development. This work discusses various useful applicable algorithms, Circular Hough Transform (CHT) as well as Continuously adaptive mean shift (Camshift) and provides some of the software solutions which can be deployed with a robotic mechanical arm to make the task of tyre changing faster, safer and more efficient. Image acquisition and software to accurately detect and classify specific objects of interest were implemented successfully, outcomes were discussed and areas for further studies suggested.