## 4 Mixed Reality for Human-Robot Interaction
### Mixed Reality-Enhanced Robotic Tele-Welding
#### 4.4.2 Mixed Reality-Enhanced Robot-Assisted Welding  
Recent research on human-centered robotic welding has focused on the development of MR-based robot-assisted welding training platforms, intuitive programming for tele- robotic welding, interactive telerobotic welding design, and MR-enhanced tele-welding paradigms. A VR-based haptic-guided welder training system was introduced in [156]. This system provides guidance to welders, simulating a human welding trainer. Both novice and skilled welders can use this platform to improve their welding skills in a virtual environment. However, this system does not integrate real welding scenarios into the virtual environment to allow welders to adjust their movements in real time according to the welding pool status, nor does it transfer human movements to the robot for actual tele-welding operations. [PERSON] et al. [157] proposed a vision-guided approach for programming automated welding robot paths in 2D, where the programmer draws the target weld pattern in the user presentation space, a low-cost camera in the system captures the image, and an algorithm detects and processes the geometry (contour lines) drawn by the human. This intuitive remote programming system for welding is limited by programming of the contour lines in two-dimensional planes only and does not have the real-time capability of a telerobotic welding system. In [158], the authors analyzed the integration of advanced technologies, such as MR, robot vision, intuitive and immersive teleoperation, and artificial intelligence (AI), to build an interactive telerobotic welding system. This paradigm enables efficient human-centered collaboration between remote welding platforms and operators through multi-channel communication. A teleoperated wall-climbing robotic welding system was developed to demonstrate the application of various technologies in an innovative robotic interaction system to best achieve natural human-robot interaction. However, the mobile wall-climbing welding robot presented in this system has a simple structure and does not have a flexible robot manipulator to mimic welders' human-level manipulation and make dexterous welding adjustments. Natural human movement signals were not used to improve the system intuitiveness and control the robot for tele-welding tasks. More recently, research attention has been focused on MR-enhanced tele-welding paradigms [159]. It was verified in [160] that there were no statistically significant differences in the total welding scores between participants in the physical welding group and the mixed reality-based welding groups. The mixed reality welding user interface gives operators the ability to perform welding at a distance while maintaining a level of manipulation [161]. An optical tracking-based telerobotic welding system was introduced in [162]. The Leap Motion sensor captures the trajectory of a virtual welding gun held by a human welder in the user space to control the remote welding robot for the welding task. However, this welding system requires the use of a physical replica of the welding workpiece in the user space to superimpose a real-time weld pool state and guide the welders to adjust their hand movements to the shape of the workpiece [163]. Thus, this MR welding system is not suitable for a wide range of workpieces. [PERSON] et al. [163] developed a projection-based MR telerobotic welding system for transferring welder skills and human-level dynamics to the welding robot (Figure 8). Human welders interact with the welding robot by moving a tracked virtual welding torch in 3D space. A UR5 industrial manipulator equipped with vision sensors is operated remotely to perform the welding task. The weld pool stream from the welding site is transmitted back to the user and projected on a mock-up of the workpiece. The human welder can monitor the work process and adjust the movements according to the projected weld pool status from the worksite.