针对远程操作中的触觉引导模型选择，提出基于环境特征的实用指南。
Selecting haptic guidance models in teleoperation: guidelines from a comparative user study
- 将常见引导模型统一为刚度阻尼系统，用特定函数描述其差异。
- 不同环境下表现各异：弹簧阻尼适合杂乱场景，势场适合空旷区，导管模型最均衡。
- 首次引入客观指标评估交互效果，引导力大小与操作者舒适度、信任感相关。
远程操作中的触觉引导通过力反馈提升操作性能。本文提出模型选择指南，需综合考虑任务、环境与操作者特征。我们建立统一框架，将弹簧阻尼、势场、导管等常见模型表述为具有特定引导函数的刚度-阻尼系统。在垂直农场任务中，对六种不同环境条件下的三种经典模型进行了用户对比实验。结果表明无绝对最优模型：弹簧阻尼在杂乱环境中表现最佳，势场在开阔空间有效但靠近障碍物时存在风险，导管模型则提供较平衡的折衷方案。本文提出新的客观评估指标，发现引导力大小与操作者舒适度和信任度显著相关。研究结果为基于环境特性及实时评估指标的模型选择提供了可落地的指导。
原文摘要 · Abstract (English)
Haptic guidance in teleoperation enhances operator performance through force feedback. This paper presents guidelines to select the most appropriate model considering the task, the environment and the operator. We define a unified formulation expressing most common models (spring-damper, potential field, and guiding tube) as variations of a stiffness-damping system with model-specific guiding functions. We conducted a user study comparing the three classical models across six scenarios with varying environmental conditions in a vertical farming task. Results show no universally superior model: spring-damper excels in cluttered environments, potential field in free spaces (but it shows risks near obstacles), and guiding tube offers a balanced compromise. We propose novel objective metrics to evaluate the interaction, and show that guiding force magnitude correlates with comfort and trust scores. These findings provide practical model selection guidelines through environmental characteristics and real-time evaluation metrics.
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