Graduate Program in Informatics, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.
Graduate Program in Electrical Engineering, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.
Sensors (Basel). 2024 Sep 25;24(19):6212. doi: 10.3390/s24196212.
Robotic walking devices can be used for intensive exercises to enhance gait rehabilitation therapies. Mixed Reality (MR) techniques may improve engagement through immersive and interactive environments. This article introduces an MR-based multimodal human-robot interaction strategy designed to enable shared control with a Smart Walker. The MR system integrates virtual and physical sensors to (i) enhance safe navigation and (ii) facilitate intuitive mobility training in personalized virtual scenarios by using an interface with three elements: an arrow to indicate where to go, laser lines to indicate nearby obstacles, and an ellipse to show the activation zone. The multimodal interaction is context-based; the presence of nearby individuals and obstacles modulates the robot's behavior during navigation to simplify collision avoidance while allowing for proper social navigation. An experiment was conducted to evaluate the proposed strategy and the self-explanatory nature of the interface. The volunteers were divided into four groups, with each navigating under different conditions. Three evaluation methods were employed: task performance, self-assessment, and observational measurement. Analysis revealed that participants enjoyed the MR system and understood most of the interface elements without prior explanation. Regarding the interface, volunteers who did not receive any introductory explanation about the interface elements were mostly able to guess their purpose. Volunteers that interacted with the interface in the first session provided more correct answers. In future research, virtual elements will be integrated with the physical environment to enhance user safety during navigation, and the control strategy will be improved to consider both physical and virtual obstacles.
机器人步行设备可用于强化训练,以增强步态康复治疗。混合现实 (MR) 技术可以通过沉浸式和互动式环境提高参与度。本文介绍了一种基于 MR 的多模态人机交互策略,旨在与智能助行器实现共享控制。MR 系统集成了虚拟和物理传感器,以(i) 增强安全导航,(ii) 通过使用具有三个元素的界面在个性化虚拟场景中促进直观的移动性训练:箭头指示行进方向,激光线指示附近障碍物,以及椭圆表示激活区域。多模态交互是基于上下文的;在导航过程中,存在附近人员和障碍物会调节机器人的行为,以简化避碰,同时允许适当的社交导航。进行了一项实验来评估所提出的策略和界面的自解释性质。志愿者被分为四组,每组在不同的条件下进行导航。采用了三种评估方法:任务绩效、自我评估和观察测量。分析表明,参与者喜欢 MR 系统,并且大多数能够在没有预先解释的情况下理解大多数界面元素。关于界面,没有收到关于界面元素的任何介绍性解释的志愿者大多能够猜测其用途。在第一会话中与界面进行交互的志愿者提供了更多正确的答案。在未来的研究中,将虚拟元素与物理环境集成,以提高导航过程中的用户安全性,并改进控制策略以同时考虑物理和虚拟障碍物。