Control of a wheelchair using an adaptive K-Means clustering of head poses

L. A. Rivera, G. DeSouza, L. D. Franklin
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引用次数: 6

Abstract

Operating a wheelchair is often a difficult task for individuals with severe disabilities. Also, with the progress of the condition, the use of most current robotic assistive technologies becomes less attractive or simply not applicable anymore. In this work, we developed a system that allows a user to operate a wheelchair using only their heads. Our method utilizes an Infrared (IR) depth sensor to capture the user's head pose, while it includes an adaptive component to the detection of that pose. The adaptation, based on a type of Re-enforcement K-Means clustering, can accommodate users with limited and changing head mobility - no matter how skewed the head motion may become with the progress of the condition. We tested the system using five test subjects, who simulated `normal' an `abnormal' motions of the head. The system worked well in all cases, and all test subjects found the interface quite intuitive.
使用头部姿态的自适应k均值聚类控制轮椅
对于有严重残疾的人来说,操作轮椅往往是一项艰巨的任务。此外,随着病情的进展,目前大多数机器人辅助技术的使用变得不那么有吸引力或根本不适用了。在这项工作中,我们开发了一个系统,允许使用者只用他们的头来操作轮椅。我们的方法利用红外(IR)深度传感器来捕捉用户的头部姿势,同时它包含一个自适应组件来检测该姿势。这种适应性基于一种强化k均值聚类,可以适应头部活动受限和不断变化的用户——无论随着病情的进展,头部运动可能变得多么扭曲。我们用五个测试对象来测试这个系统,他们分别模拟头部的“正常”和“异常”运动。该系统在所有情况下都运行良好,所有测试对象都觉得界面非常直观。
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