400  ms。  The  system  employed  one  CSS Weld-Sensor

Fig。 9 Robotic arc welding with Power-Trac (Servo Robot Inc 2013b)

  to  measure  the  true  position  of  the  seam  prior    to

welding, allowing optimization of the programmed weld path by automatic correction for component tol- erances and fit-up variation (Nomura et al。 1986)。

ABB Weldguide III Weldguide III is a through-the-arc seam-tracking sensor developed by ABB that uses two external sensors for the welding current and arc  voltage。 It has a measurement capacity at  25,000  Hz  for quick and accurate path corrections and can be integrated with various transfer modes, like spray-arc, short-arc, and pulsed-arc GMAW。

Weldguide III has basic, advanced, and multi-pass modes of tracking。 The basic tracking modes consist of either torch-to-work mode or centerline mode。 In torch- to-work mode, height is sensed, and in fixed torch-to- work, distance is maintained by measuring the target current and adjusting the height to maintain the  setting,

as shown in Fig。 12a。 Centerline mode is used with weaving, where the impedance is measured as the torch moves from side-to-side using the bias parameter, as il- lustrated in Fig。 12b (ABB Group 2010)。

In adaptive fill mode, a type of  advanced  tracking mode, the robot  can  identify  and  adjust  for  variations in joint tolerances。 If the joint changes in width, the robot’s weave will increase or decrease and travel speed is adjusted accordingly as shown in Fig。  13。

For multi-pass welding, Weldguide III tracks the first pass and stores the actual tracked path so that  it  can offset for subsequent passes, as shown in Fig。   14。

A practical case:  MARWIN

Targeted problem

Currently available welding technologies such as manual welding  and  welding  robots  have  several     drawbacks。

Manual welding is time-consuming, while existing robot are not efficient enough for manufacturing small batch- sized products but they also often face  discrepancies when reprogramming is  necessary。  This reprogramming is also extremely time-consuming。

A project named MARWIN, a part of the European Research Agency FP7  project  framework,  was initiated in November 2011 (CORDIS 2015)。 Its aim was to de- velop a vision-based welding robot suitable for small- and medium-sized enterprises (SMEs) with automatic track calculation, welding parameter selection, and an embedded quality control system (Chen et al。 2007)。 MARWIN can extract welding parameters and  calcu- late the trajectory of the end effector directly from the CAD models, which are then verified by real-time 3D scanning and registration (Rodrigues et al。 2013a)。 The main problem for SMEs trying to use robotic welding is that products are changed after small batches and the extensive reprogramming necessary is expensive and time-consuming。 Limitations of current OLP include manufacturing tolerances between CAD and  work- pieces   and   inaccuracies   in   workpiece   placement and

modeled work cell (TWI Ltd  2012)。  Figure  15  shows the overall process diagram for the MARWIN   system。

Programming

The MARWIN system consists of a control  computer with a user interface and controls for the vision system and the welding robot。 The new methodology for robotic offline programming (OLP) addressing the issue of auto- matic program generation directly from 3D CAD models and verification through online 3D reconstruction。 The vision system is capable of reconstructing a 3D image of parts using structured light and pattern recognition, which is then compared to a CAD drawing of the real assembly。 It extracts welding parameters and calculates robot trajectories directly from CAD models which are then verified by real-time 3D scanning and registration。 The computer establishes the best robotic trajectory based on the user input。 Automatic adjustments to the trajectory are done from the reconstructed image。 The welding parameters are automatically chosen from an in- built database of weld procedures (TWI Ltd 2012)。 The user’s role is limited to high-level specification of the welding task and confirmation and/or modification of weld    parameters    and    sequences    as    suggested   by