Abstract
This paper presents an approach for the automatic detection and fast 3D profiling of lateral body panels of vehicles. The work introduces a method to integrate raw streams from depth sensors in the task of 3D profiling and reconstruction and a methodology for the extrinsic calibration of a network of Kinect sensors. This sensing framework is intended for rapidly providing a robot with enough spatial information to interact with automobile panels using various tools. When a vehicle is positioned inside the defined scanning area, a collection of reference parts on the bodywork are automatically recognized from a mosaic of color images collected by a network of Kinect sensors distributed around the vehicle and a global frame of reference is set up. Sections of the depth information on one side of the vehicle are then collected, aligned, and merged into a global RGB-D model. Finally, a 3D triangular mesh modelling the body panels of the vehicle is automatically built. The approach has applications in the intelligent transportation industry, automated vehicle inspection, quality control, automatic car wash systems, automotive production lines, and scan alignment and interpretation.
Highlights
Robot manipulation and navigation require efficient methods for representing and interpreting the surrounding environment
This work contributes to the robotic vision field by proposing a simple and efficient methodology for automatic 3D surface modeling of large vehicle parts via the coordinated and integrated operation of several RGB-D sensor heads; a dedicated methodology for extrinsic calibration of Kinect sensors, as well as a rapid algorithm for triangle meshing Journal of Sensors which takes advantage of the structure of the point clouds provided by the Kinect sensors
The 3D modeling results are meant to provide a robotic arm with sufficiently accurate spatial information about the bodywork of a vehicle and the 3D location of up to fourteen features of interest over the surface such that it can interact with the automobile panels for various inspection or maintenance tasks
Summary
Robot manipulation and navigation require efficient methods for representing and interpreting the surrounding environment. Robots working in dynamic environments demand reliable methods to interpret their surroundings and are submitted to severe time constraints. Most existing solutions for robotic environment representation and interpretation make use of high-cost 3D profiling cameras, scanners, sonars, or combinations of them, which often result in lengthy acquisition and slow processing of massive amounts of information. The method presented in this work uses a set of Kinect depth sensors properly calibrated to collect visual information as well as. This work contributes to the robotic vision field by proposing a simple and efficient methodology for automatic 3D surface modeling of large vehicle parts via the coordinated and integrated operation of several RGB-D sensor heads; a dedicated methodology for extrinsic calibration of Kinect sensors, as well as a rapid algorithm for triangle meshing. Journal of Sensors which takes advantage of the structure of the point clouds provided by the Kinect sensors
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
