隨著近來擴增實境(Augmented Reality, AR)技術已蓬勃發展，成功應用於教育、醫療、軍事、工業與娛樂等領域，輔助進行相關的人工作業。如何透過擴增實境產生即時性互動功能，有效提高作業效能，仍欠缺較完整的介面設計準則。人工沿邊作業(Trajectory Tracking Task)常見於製造現場的機器人示範編程，以及醫療外科手術的輔助性工具，過往已提出不同感官回饋形式，但仍缺乏之間完整的績效比較，無法達成互動介面的效益最佳化。本研究針對擴增實境中，根據真實軌跡之人工沿邊作業，進行深入的人因評估實驗，根據多項量化評估指標，比較不同感官回饋方式，於輔助沿邊作業的績效表現。根據實驗結果分析顯示，於困難度較高的沿邊作業中，回饋資訊除了提供錯誤狀態提示，亦應給予受試者動作的修正建議；此外，相較於視覺與聽覺，觸覺回饋資訊顯示出最佳適配性。受試者傾向在較困難的作業中，仰賴即時回饋資訊完成作業，因此推測應採用確認回饋資訊設計，適當主動介入作業行為。最後發現人工沿邊作業中，對於判斷是否在可接受軌跡範圍內，會受到受試者作業姿勢的影響，而改變作業的績效表現，故建議設計輔助性功能時，應考量操作姿勢的限制。本研究獲得之實驗結果與發現，能提供於擴增實境功能中，人工作業輔助性介面設計的參考依據。

Augmented Reality (AR) technology has made a significant progress in recent years with AR applications successfully applied to assist manual operations in various industries like manufacturing, military, education, and entertainment. However, there is still a lack of design guidelines for engineers to develop AR user interfaces that can effectively enhance user's situation awareness with instant sensory feedback. Manual trajectory tracking frequently occurs in robot programming by demonstration in manufacturing and major surgical operations. AR functions and interfaces have been developed to assist manual trajectory tracking tasks. These functions may not be optimal design without in-depth comparisons among the effectiveness of different sensory feedbacks employed in the interfaces. Therefore, this work aims to conduct ergonomic assessment for AR user interfaces with different sensory feedback designed to assist manual trajectory tracking. The focus is to thoroughly compare different sensory feedback designs with quantitative measures. According to experimental results, not only should the feedback information displayed in the AR interface signify the occurrence of tracking errors, but it could also constantly suggest the user corrective actions. Moreover, tactile sensory feedback outperforms the visual and audio ones, as the user tends to rely on the haptic feedback force to complete the task, especially for the tracking task of high complexity. Lastly, the user's holding posture of the tracking pen influences the task performance when the tracking accuracy falls into an acceptable range. Thus, AR assisted functions need to consider this factor in optimal interface design. The findings obtained by this work provide useful insights into sensory feedback designs in AR assisted functions developed for manual trajectory tracking.

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