Name
Abstract | ||
|---|---|---|
Training technicians to acquire new maintenance and assembly skills is important for various industries. Because maintenance and assembly tasks can be very complex, training technicians to efficiently perform new skills is challenging. Training of this type can be supported by Augmented Reality, a powerful industrial training technology that directly links instructions on how to perform the service tasks to the machine parts that require processing. Because of the increasing complexity of maintenance tasks, it is not sufficient to train the technicians in task execution. Instead, technicians must be trained in the underlying skills-sensorimotor and cognitive-that are necessary for the efficient acquisition and performance of new maintenance operations. These facts illustrate the need for efficient training systems for maintenance and assembly skills that accelerate the technicians' acquisition of new maintenance procedures. Furthermore, these systems should improve the adjustment of the training process for new training scenarios and enable the reuse of worthwhile existing training material. In this context, we have developed a novel concept and platform for multimodal Augmented Reality-based training of maintenance and assembly skills, which includes sub-skill training and the evaluation of the training system. Because procedural skills are considered as the most important skills for maintenance and assembly operations, we focus on these skills and the appropriate methods for improving them. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.robot.2012.09.013 | Robotics and Autonomous Systems |
Keywords | Field | DocType |
Augmented reality,Multimodal interaction,Haptic rendering,Maintenance training | Multimodal interaction,Haptic rendering,Reuse,Simulation,Training system,Computer science,Augmented reality | Journal |
Volume | Issue | ISSN |
61 | 4 | 0921-8890 |
Citations | PageRank | References |
47 | 2.07 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sabine Webel | 1 | 140 | 10.90 |
| Uli Bockholt | 2 | 94 | 5.15 |
| Timo Engelke | 3 | 255 | 22.48 |
| Nirit Gavish | 4 | 97 | 6.32 |
| Manuel Olbrich | 5 | 101 | 8.85 |
| Carsten Preusche | 6 | 159 | 16.23 |