Human skill capture: A Hidden Markov Model of force and torque data in peg-in-a-hole assembly process

Zhao, Yuchen; Al-Yacoub, Ali; Goh, Yeh Huann; Justham, Laura; Lohse, Niels; Jackson, Mats

doi:10.1109/smc.2016.7844315

Cited by 12 publications

(11 citation statements)

References 17 publications

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“…The 'alignment and insert'-task is rated as moderate based on the variability score. Similar findings can be found as a significant amount of research uses special insertion tasks in the field of control mechanism based on counterforce (see, for example, Zhao et al 2016). The final fastening task also suits a low level of automation because of the intricacy in avoiding a cross-threading scenario in automation.…”

Section: Automation Decision Supportsupporting

confidence: 80%

A variability taxonomy to support automation decision-making for manufacturing processes

Goh

Micheler

Sanchez-Salas

et al. 2019

Production Planning & Control

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Although many manual operations have been replaced by automation in the manufacturing domain in various industries, skilled operators still carry out critical manual tasks such as final assembly. The business case for automation in these areas is difficult to justify due to increased complexity and costs arising out of process variabilities associated with those tasks. The lack of understanding of process variability in automation design means that industrial automation often does not realize the full benefits at the first attempt, resulting in the need to spend additional resource and time, to fully realize the potential. This article describes a taxonomy of variability when considering the automation of manufacturing processes. Three industrial case studies were analyzed to develop the proposed taxonomy. The results obtained from the taxonomy are discussed with a further case study to demonstrate its value in supporting automation decision-making.

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Section: Automation Decision Supportsupporting

confidence: 80%

A variability taxonomy to support automation decision-making for manufacturing processes

Goh

Micheler

Sanchez-Salas

et al. 2019

Production Planning & Control

View full text Add to dashboard Cite

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“…Machine learning Task demonstration Works rather on action than on process level Zhao et al (2016) Learning from demo Discrete Hierarchical task analysis (HTA)…”

Section: Continuousmentioning

confidence: 99%

A transformation of human operation approach to inform system design for automation

2020

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Design of automation system relies on experts' knowledge and experience accumulated from past solutions. In designing novel solutions, however, it is difficult to apply past knowledge and achieve design right-first-time, therefore wasting valuable resources and time. SADT/IDEF0 models are commonly used by automation experts to model manufacturing systems based on the manual process. However, function generalisation without benchmarking is difficult for experts particularly for complex and highly skilled-based tasks. This paper proposes a functional task abstraction approach to support automation design specification based on human factor attributes. A semi-automated clustering approach is developed to identify key functions from an observed manual process. The proposed approach is tested on five different automation case studies. The results indicate the proposed method reduces inconsistency in task abstraction when compared to the current approach that relies on the experts, which are further validated against the solutions generated by automation experts.

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“…Secondly, although the LM is up to sub-millimeter accuracy, it still cannot meet the requirements of a tight tolerant assembly task where the error is in micrometer range. Thirdly, the LM has a limited sensing range, and it cannot be applied to tasks with large workspace; finally, like other non-contact interaction methods, the lack of force feedback makes it difficult to be applied in compliant tasks, which are common in complex assembly processes [22,23].…”

Section: Introductionmentioning

confidence: 99%

A Gesture-Based Teleoperation System for Compliant Robot Motion

et al. 2019

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Currently, the gesture-based teleoperation system cannot generate precise and compliant robot motions because human motions have the characteristics of uncertainty and low-resolution. In this paper, a novel, gesture-based teleoperation system for compliant robot motion is proposed. By using the left hand as the commander and the right hand as a positioner, different operation modes and scaling ratios can be tuned on-the-fly to meet the accuracy and efficiency requirements. Moreover, a vibration-based force feedback system was developed to provide the operator with a telepresence capability. The pick-and-place and peg-in-hole tasks were used to test the effectiveness of the teleoperation system we developed. The experiment results prove that the gesture-based teleoperation system is effective at handling compliant robot motions.

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Human skill capture: A Hidden Markov Model of force and torque data in peg-in-a-hole assembly process

Cited by 12 publications

References 17 publications

A variability taxonomy to support automation decision-making for manufacturing processes

A variability taxonomy to support automation decision-making for manufacturing processes

A transformation of human operation approach to inform system design for automation

A Gesture-Based Teleoperation System for Compliant Robot Motion

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