Robot-Assisted Immersive Kinematic Experience Transfer for Welding Training
Yang Ye, Tianyu Zhou, Jing Du
- 发表年份
- 2023
- 引用次数
- 37
摘要
Human motor skills are critical for executing a variety range of tasks in construction. Traditional hands-on training is resource and labor intensive, whereas virtual training, such as video demonstrations, cannot provide trainees with egocentric kinesthetic or proprioceptive experience such as muscular engagement. It is important to develop remote training methods that can provide rich sensory feedback and leverage the trainee’s proprioception. This paper proposes a novel remote motor skill training system that can transfer experts’ kinematic and kinesthetic experience, including both positional and force experience, to novice trainees by using virtual reality (VR) and a robot arm without the physical presence of the experts. The system uses VR to simulate virtual operation scenarios and interactions to provide an immersive operation experience. The robotic system records experts’ kinematic and kinesthetic patterns and trains novices with perceptual learning. The system design was demonstrated with a welding training task. A welding simulator was built with a Unity engine and a seven-degrees-of-freedom robot arm, which provided high-fidelity welding experience and could actively guide welding trainees. It was found that the welding simulator was resilient to external disturbance and provided accurate feedback and guidance. The proposed system contributes to the design of a more embodied remote motor skill training method.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991