This study addresses the challenge of low dexterity in teleoperation tasks caused by limited sensory feedback and visual occlusion. We propose a novel approach that integrates haptic feedback into teleoperation using the adaptive triggers of a commercially available DualSense controller. By adjusting button stiffness based on the proximity of objects to the robot's end effector, the system provides intuitive, real-time feedback to the operator. To achieve this, the effective volume of the end effector is virtually expanded, allowing the system to predict interactions by calculating overlap with nearby objects. This predictive capability is independent of the user's intent or the robot's speed, enhancing the operator's situational awareness without requiring complex pre-programmed behaviors. The stiffness of the adaptive triggers is adjusted in proportion to this overlapping volume, effectively conveying spatial proximity and movement cues through an "one degree of freedom" haptic feedback mechanism. Compared to existing solutions, this method reduces hardware requirements and computational complexity by using a geometric simplification approach, enabling efficient operation with minimal processing demands. Simulation results demonstrate that the proposed system reduces collision risk and improves user performance, offering an intuitive, precise, and safe teleoperation experience despite real-world uncertainties and communication delays.

翻译：本研究针对远程操作任务中因感官反馈受限和视觉遮挡导致的灵活性不足问题，提出一种创新方案，将触觉反馈整合到远程操作中。该方案利用市售DualSense控制器的自适应扳机键，根据物体与机器人末端执行器的接近程度动态调整按键刚度，从而为操作者提供直观的实时反馈。为实现这一目标，系统通过虚拟扩展末端执行器的有效体积，计算其与邻近物体的重叠区域来预测交互行为。这种预测能力独立于用户意图或机器人运动速度，无需复杂的预编程行为即可增强操作者的环境感知能力。自适应扳机键的刚度根据重叠体积按比例调节，通过"单自由度"触觉反馈机制有效传递空间接近度与运动信息。与现有方案相比，本方法采用几何简化策略降低了对硬件配置与计算复杂度的要求，能以最小处理需求实现高效运行。仿真实验表明，所提出的系统能降低碰撞风险并提升用户操作性能，在现实环境的不确定性与通信延迟条件下，仍能提供直观、精准且安全的远程操作体验。