用眼神预测操作意图，动态调整机器人辅助力度。
The Use of Gaze-Derived Confidence of Inferred Operator Intent in Adjusting Safety-Conscious Haptic Assistance
- 通过眼神预判操作者目标，实时生成引导力。
- 结合信心值调节辅助强度，提升任务准确率与速度。
- 适合远程操控、高危场景下的人机协作应用。
在危险或高风险环境中，人类直接执行任务往往不可行，因此越来越多任务由遥操作机器人完成。然而，由于缺乏触觉反馈和视频画面深度不足，操作者易产生与机器人脱节的感觉。为此，系统主动推断操作者的意图，并基于预测结果提供辅助。创新性地引入眼神数据计算意图置信度，动态调整人机协同控制。操作者在开始操控前通过注视目标区域，系统利用势场法生成指向目标的引导力，同时设置安全边界以降低损伤风险。根据意图置信度调节辅助强度，使控制更自然，增强机器人对操作者意图的理解。初步验证结果显示，该系统可提升任务准确性、缩短执行时间并减少操作错误。
原文摘要 · Abstract (English)
Humans directly completing tasks in dangerous or hazardous conditions is not always possible where these tasks are increasingly be performed remotely by teleoperated robots. However, teleoperation is difficult since the operator feels a disconnect with the robot caused by missing feedback from several senses, including touch, and the lack of depth in the video feedback presented to the operator. To overcome this problem, the proposed system actively infers the operator's intent and provides assistance based on the predicted intent. Furthermore, a novel method of calculating confidence in the inferred intent modifies the human-in-the-loop control. The operator's gaze is employed to intuitively indicate the target before the manipulation with the robot begins. A potential field method is used to provide a guiding force towards the intended target, and a safety boundary reduces risk of damage. Modifying these assistances based on the confidence level in the operator's intent makes the control more natural, and gives the robot an intuitive understanding of its human master. Initial validation results show the ability of the system to improve accuracy, execution time, and reduce operator error.
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