Kinesthetic Robot Force Response enhanced by the Laws of Physics

Gradmann, Michael; Wölfel, Kim; Henrich, Dominik

doi:10.1109/roman.2018.8525812

Cited by 1 publication

(1 citation statement)

References 17 publications

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“…As a result, systems like this are unsuitable for tasks requiring precision. Other automatic spatial perception methods based on object detection are limited to specific applications, such as empty plane (Gradmann et al, 2018), marker placement (Lin et al, 2017), and additional precise cameras (Bambuŝek et al, 2019). Additionally, automatic algorithms for object detection and registration are timeconsuming and hard to perform in real-time (Makhataeva & Varol, 2020).…”

Section: Ar-based Robot Programmingmentioning

confidence: 99%

HA$$R^{2}$$bot: a human-centered augmented reality robot programming method with the awareness of cognitive load

2023

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In the era of Industry 4.0, manufacturing enterprises are actively adopting collaborative robots (Cobots) in their productions. Current online and offline robot programming methods are difficult to use and require extensive experience or skills. On the other hand, the manufacturing industries are experiencing a labor shortage. An essential question, therefore, is: how would a new robot programming method help novice users complete complex tasks effectively, efficiently, and intuitively? To answer this question, we proposed HA bot, a novel human-centered augmented reality programming interface with awareness of cognitive load. Using NASA’s system design theory and the cognitive load theory, a set of guidelines for designing an AR-based human-robot interaction system is obtained through a human-centered design process. Based on these guidelines, we designed and implemented a human-in-the-loop workflow with features for cognitive load management. The effectiveness and efficiency of HA bot are verified in two complex tasks compared with existing online programming methods. We also evaluated HA bot quantitatively and qualitatively through a user study with 16 participants. According to the user study, compared with existing methods, HA bot has higher efficiency, a lower overall cognitive load, lower cognitive loads for each type, and higher safety.

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Section: Ar-based Robot Programmingmentioning

confidence: 99%