Hernandez-Gobertti Fernando, Kudyk Ivan D, Lozano Raul, Nguyen Giang T, Gomez-Barquero David
iTEAM Research Institute, Universitat Politècnica de València (UPV), 46022 Valencia, Spain.
Wandelbots GmbH, Technische Univeristät Dresden, 01159 Dresden, Germany.
Sensors (Basel). 2025 Jun 26;25(13):3993. doi: 10.3390/s25133993.
This study presents a novel investigation into immersive teleoperation systems using collaborative, device-agnostic interfaces for advancing smart haptics in industrial assistive applications. The research focuses on evaluating the quality of experience (QoE) of users interacting with a teleoperation system comprising a local robotic arm, a robot gripper, and heterogeneous remote tracking and haptic feedback devices. By employing a modular device-agnostic framework, the system supports flexible configurations, including one-user-one-equipment (1U-1E), one-user-multiple-equipment (1U-ME), and multiple-users-multiple-equipment (MU-ME) scenarios. The experimental set-up involves participants manipulating predefined objects and placing them into designated baskets by following specified 3D trajectories. Performance is measured using objective QoE metrics, including temporal efficiency (time required to complete the task) and spatial accuracy (trajectory similarity to the predefined path). In addition, subjective QoE metrics are assessed through detailed surveys, capturing user perceptions of presence, engagement, control, sensory integration, and cognitive load. To ensure flexibility and scalability, the system integrates various haptic configurations, including (1) a Touch kinaesthetic device for precision tracking and grounded haptic feedback, (2) a DualSense tactile joystick as both a tracker and mobile haptic device, (3) a bHaptics DK2 vibrotactile glove with a camera tracker, and (4) a SenseGlove Nova force-feedback glove with VIVE trackers. The modular approach enables comparative analysis of how different device configurations influence user performance and experience. The results indicate that the objective QoE metrics varied significantly across device configurations, with the Touch and SenseGlove Nova set-ups providing the highest trajectory similarity and temporal efficiency. Subjective assessments revealed a strong correlation between presence and sensory integration, with users reporting higher engagement and control in scenarios utilizing force feedback mechanisms. Cognitive load varied across the set-ups, with more complex configurations (e.g., 1U-ME) requiring longer adaptation periods. This study contributes to the field by demonstrating the feasibility of a device-agnostic teleoperation framework for immersive industrial applications. It underscores the critical interplay between objective task performance and subjective user experience, providing actionable insights into the design of next-generation teleoperation systems.
本研究对沉浸式遥操作系统进行了一项新颖的调查,该系统使用协作式、设备无关接口来推进工业辅助应用中的智能触觉。研究重点是评估用户与一个遥操作系统交互时的体验质量(QoE),该遥操作系统包括一个本地机器人手臂、一个机器人夹具以及异构远程跟踪和触觉反馈设备。通过采用模块化的设备无关框架,该系统支持灵活配置,包括单用户单设备(1U-1E)、单用户多设备(1U-ME)和多用户多设备(MU-ME)场景。实验设置包括让参与者操纵预定义的物体,并按照指定的3D轨迹将它们放入指定的篮子中。使用客观的QoE指标来衡量性能,包括时间效率(完成任务所需的时间)和空间精度(与预定义路径的轨迹相似度)。此外,通过详细调查来评估主观QoE指标,获取用户对临场感、参与度、控制、感官整合和认知负荷的感知。为确保灵活性和可扩展性,该系统集成了各种触觉配置,包括:(1)用于精确跟踪和基于地面的触觉反馈的触觉动觉设备;(2)作为跟踪器和移动触觉设备的DualSense触觉操纵杆;(3)带有摄像头跟踪器的bHaptics DK2振动触觉手套;(4)带有VIVE跟踪器的SenseGlove Nova力反馈手套。这种模块化方法能够对不同设备配置如何影响用户性能和体验进行比较分析。结果表明,客观的QoE指标在不同设备配置之间有显著差异,Touch和SenseGlove Nova设置提供了最高的轨迹相似度和时间效率。主观评估显示临场感和感官整合之间有很强的相关性,用户在使用力反馈机制的场景中报告了更高的参与度和控制感。认知负荷在不同设置中有所不同,更复杂的配置(如1U-ME)需要更长的适应期。本研究通过证明用于沉浸式工业应用的设备无关遥操作框架的可行性,为该领域做出了贡献。它强调了客观任务性能和主观用户体验之间的关键相互作用,为下一代遥操作系统的设计提供了可操作的见解。