Welding seam recognition and tracking for a novel mobile welding robot based on multi-layer sensing strategy

Mobile welding robot with adaptive seam tracking ability can greatly improve the welding efficiency and quality, which has been extensively studied. To further improve the automation in multiple station welding, a novel intelligent mobile welding robot consists of a four-wheeled mobile platform and a collaborative manipulator is developed. Under the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operation. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, the multi-layer sensing strategy is performed to ensure the welding seam can be detected and tracked with high precision. By applying hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Then a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively in different station. Also, the multiple station welding efficiency can be improved and quality can also be guaranteed.

Design of controller for mobile robot in welding process of shipbuilding engineering

The present study describes the development of control hardware and software for a mobile welding robot. This robot is able to move and perform welding tasks in a double hull structure. The control hardware consists of a main controller and a welding machine controller. Control software consists of four layers. Each layer consists of modules. Suitable combinations of modules enable the control software to perform the required tasks. Control software is developed using C programming under QNX operating system. For the modularizing architecture of control software, we designed control software with four layers: Task Manager, Task Planner, Actions for Task, and Task Executer. The embedded controller and control software was applied to the mobile welding robot for successful execution of the required tasks. For evaluate this imbedded controller and control software, the field tests are conducted, it is confirmed that the developed imbedded controller of mobile welding robot for shipyard is well designed and implemented.

Localization and tracking control for mobile welding robot

Purpose – The purpose of this paper is to design the localization and tracking algorithms for our mobile welding robot to carry out the large steel structure welding operations in industrial environment. Design/methodology/approach – Extended Kalman filter, considering the bicycle-modeled robot, is adopted in the localization algorithm. The position and orientation of our mobile welding robot is estimated using the feedback of the laser sensor and the robot motion commands history. A backstepping variable is involved in the tracking algorithm. By introducing a specifically selected Lyapunov function, we proved the tracking algorithm using Barbalat Lemma, which leads the errors of estimated robot states to converge to zero. Findings – The experiments show that the proposed localization method is fast and accurate and the tracking algorithm is robust to track straight lines, circles and other typical industrial curve shapes. The proposed localization and tracking algorithm could be used, but not limited to the mobile welding. Originality/value – Localization problem which is neglected in previous research is very important in mobile welding. The proposed localization algorithm could estimate the robot states timely and accurately, and no additional sensors are needed. Furthermore, using the estimated robot states, we proposed and proved a tracking algorithm for bicycle-modeled mobile robots which could be used in welding as well as other industrial operation scenarios.