Session: MR-07-02

Paper Number: 143205

143205 - Automated Weld Path Generation in Cluttered Environments Using Segmentation and Iterative Closest Point Workpiece Localization 

A significant amount of manufacturing is performed by small to medium enterprises (SMEs), but these manufacturers often have lower adoption rates of automation. The cost and complexity associated with traditional robot systems slows the adoption of robotic welding operations for SMEs. The recent increase in collaborative robot (cobot) welding systems is bridging the gap however, by reducing the complexity of installing, maintaining and training operators to perform weld operations with cobots. These systems add flexibility in range of operator use and ease of deployment. These systems however still rely on kinematic registration between the robot-mounted torch and workpiece on any open-loop weld. This requires precise placement of the workpiece prior to preforming a weld. This work will discuss a method for part identification and registration in a welding task as a step toward automated weld path generation. The method is based on lower-resolution 3D cameras (RGBD cameras) using a combination of color and depth information. This information is used to both identify the workpiece within a workspace that may have other, non-workpiece items, and then provide  registration or localization information of the workpiece within a resolution that could allow follow-on near-position strategies to achieve final weld-path identification. The procedure is defined and then evaluated on a prototype cobot welding system.

Presenting Author: Stephen Canfield Tennessee Technological University

Presenting Author Biography: Stephen Canfield is a professor in the department of Mechanical Engineering at Tennessee Tech. He received his PhD in robotics applications from Virginia Tech.

Authors:

Tristan Hill Tennessee Technological University
Hyung-Jin Yoon Tennessee Technological University
Stephen Canfield Tennessee Technological University