Autonomous metrology for robot mounted 3D vision systems. Issue 1 (2017)

• Record Type: Journal Article
• Authors: Kinnell, Peter; Rymer, Tom; Hodgson, John; Justham, Laura; Jackson, Mike
• Is Part Of: CIRP annals. Volume 66:Issue 1(2017)
• Page Start: 483
• Page End: 486
• Publication Date: 2017
• Subjects: Metrology -- Cognitive robotics -- 3D image processing; Production engineering -- Research -- Periodicals; 670.5
• DOI: 10.1016/j.cirp.2017.04.069
• Languages: English
• ISSNs: 0007-8506

Abstract

Abstract: Using a metrology system simulation approach, an algorithm is presented to determine the best position for a robot mounted 3D vision system. Point cloud data is simulated, taking into account sensor performance, to create a ranked list of the best camera positions. These can be used by a robot to autonomously determine the most advantageous camera position for locating a target object. The algorithm is applied to an Ensenso active stereo 3D camera. Results show that when used in combination with a RANSAC object recognition algorithm, it increased positional precision by two orders of magnitude, from worst to best case.