The Influence of Interaction Technology on the Learning of Assembly Tasks Using Virtual Reality

Abstract

This paper focuses on the use of virtual reality (VR) systems for teaching industrial assembly tasks and studies the influence of the interaction technology on the learning process. The experiment conducted follows a between-subjects design with 60 participants distributed in five groups. Four groups were trained on the target assembly task with a VR system, but each group used a different interaction technology: mouse-based, Phantom Omni® haptic, and two configurations of the Markerless Motion Capture (Mmocap) system (with 2D or 3D tracking of hands). The fifth group was trained with a video tutorial. A post-training test carried out the day after evaluated performance in the real task. The experiment studies the efficiency and effectiveness of each interaction technology for learning the task, taking in consideration both quantitative measures (such as training time, real task performance, evolution from the virtual task to real one), and qualitative data (user feedback from a questionnaire). Results show that there were no significant differences in the final performance among the five groups. However, users trained under mouse and 2D-tracking Mmocap systems took significantly less training time than the rest of the virtual modalities. This brings out two main outcomes: (1) the perception of collisions using haptics does not increase the learning transfer of procedural tasks demanding low motor skills and (2) Mmocap-based interactions can be valid for training this kind of tasks.

A Review of the Capabilities of Current Low-Cost Virtual Reality Technology and Its Potential to Enhance the Design Process

“…Given the need for alternative methods of interaction, many different methods and devices have been developed and tested. Past methods include wands [71,72], sensor-gloves [16,73,74], force-balls [75] and joysticks [16,37], voice command [37,76], and marked/markerless IR camera systems [77][78][79][80]. More recently, the markerless IR camera systems have been shrunk into consumer products such as the Leap Motion TM Controller and Microsoft Kinect V R .…”

An Unsupervised Machine Learning Approach to Assessing Designer Performance During Physical Prototyping

“…Verlinden and Horváth examined interactive prototyping through AR in the form of hints for specific applications [32], and Fiorentino et al [33] proposed an augmented reality approach for manipulation of CAD designs. Notably, Vélaz et al applied VR technology to the field of assembly learning, with participants learning how to assemble a product in several different modes [34]. While this attempted to solve a similar problem, it was primarily concerned with task completion, rather than assessment, and found that no improvement was offered by virtual environments.…”

“…Of these works which focused on task learning, the application to an engineering design space were limited (with the exception of [34]). The method presented in this paper will aid in task learning by learning and inferring a user's intent.…”

Digital Factory and Virtual Reality: Teaching Virtual Reality Principles with Game Engines

“…Study [13] compares input devices. In a study with 36 participants, it was found that users interacting with a virtual environment using gestures and touch control performed better than those using a mouse, although they took longer to train.…”