Development and Performance Evaluation of Image-Based Robotic Waxing System for Detailing Automobiles

Waxing is an important aspect of automobile detailing, aimed at protecting the finish of the car and preventing rust. At present, this delicate work is conducted manually due to the need for iterative adjustments to achieve acceptable quality. This paper presents a robotic waxing system in which surface images are used to evaluate the quality of the finish. An RGB-D camera is used to build a point cloud that details the sheet metal components to enable path planning for a robot manipulator. The robot is equipped with a multi-axis force sensor to measure and control the forces involved in the application and buffing of wax. Images of sheet metal components that were waxed by experienced car detailers were analyzed using image processing algorithms. A Gaussian distribution function and its parameterized values were obtained from the images for use as a performance criterion in evaluating the quality of surfaces prepared by the robotic waxing system. Waxing force and dwell time were optimized using a mathematical model based on the image-based criterion used to measure waxing performance. Experimental results demonstrate the feasibility of the proposed robotic waxing system and image-based performance evaluation scheme.