4.6 Article

An Augmented Reality Serious Game for Learning Intelligent Wheelchair Control: Comparing Configuration and Tracking Methods

期刊

SENSORS
卷 22, 期 20, 页码 -

出版社

MDPI
DOI: 10.3390/s22207788

关键词

remote collaboration; augmented reality; Industry 4; 0; maintenance authoring tool; visual characteristics; human-centered design; user study

资金

  1. European Regional Development Fund [POCI-01-0247-FEDER-39898]
  2. IEETA
  3. Foundation for Science and Technology (FCT) [UIDB/00127/2020]

向作者/读者索取更多资源

This study introduces an augmented reality serious game to assist individuals with motor disabilities in controlling robotic wheelchairs. Two user studies were conducted to compare the effectiveness of configuring the environment using different devices and tracking capabilities. Results showed that configuring the environment with a computer was more efficient, while cloud anchors for motion tracking were more accurate.
This work proposes an augmented reality serious game (ARSG) for supporting individuals with motor disabilities while controlling robotic wheelchairs. A racing track was used as the game narrative; this included restriction areas, static and dynamic virtual objects, as well as obstacles and signs. To experience the game, a prior configuration of the environment, made through a smartphone or a computer, was required. Furthermore, a visualization tool was developed to exhibit user performance while using the ARSG. Two user studies were conducted with 10 and 20 participants, respectively, to compare (1) how different devices enable configuring the ARSG, and (2) different tracking capabilities, i.e., methods used to place virtual content on the real-world environment while the user interacts with the game and controls the wheelchair in the physical space: C1-motion tracking using cloud anchors; C2-offline motion tracking. Results suggest that configuring the environment with the computer is more efficient and accurate, in contrast to the smartphone, which is characterized as more engaging. In addition, condition C1 stood out as more accurate and robust, while condition C2 appeared to be easier to use.

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