rob@work: Robot assistant in industrial environments

Helms, Evert; Schraft, Rolf Dieter; Hägele, Martin

doi:10.1109/roman.2002.1045655

Cited by 126 publications

(80 citation statements)

References 2 publications

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“…The work in [10] provides an assistance system for the automation of the secondary assembly process "testing" with a special focus on completeness and correctness. The work in [11] is a major project for the implementation of a software framework for assembling assistive robots with a similar function as in [12][13][14][15] or as addressed in numerous other projects.…”

Section: Human-robot Interaction In the Industrial Environmentmentioning

confidence: 99%

“…The context should be analyzed in the very beginning to know which factors affect the product development, so UCD activities can be better tailored to development phases [13]. To get knowledge of the context, several methods can be applied, e.g., participating in training sessions [23], by means of a contextual inquiry or an ethnographic approach [14].…”

Section: User-centered Development and Evaluationmentioning

confidence: 99%

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First Application of Robot Teaching in an Existing Industry 4.0 Environment: Does It Really Work?

et al. 2016

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This article reports three case studies on the usability and acceptance of an industrial robotic prototype in the context of human-robot cooperation. The three case studies were conducted in the framework of a two-year project named AssistMe, which aims at developing different means of interaction for programming and using collaborative robots in a user-centered manner. Together with two industrial partners and a technological partner, two different application scenarios were implemented and studied with an off-the-shelf robotic system. The operators worked with the robotic prototype in laboratory conditions (two days), in a factory context (one day) and in an automotive assembly line (three weeks). In the article, the project and procedures are described in detail, including the quantitative and qualitative methodology. Our results show that close human-robot cooperation in the industrial context needs adaptive pacing mechanisms in order to avoid a change of working routines for the operators and that an off-the-shelf robotic system is still limited in terms of usability and acceptance. The touch panel, which is needed for controlling the robot, had a negative impact on the overall user experience. It creates a further intermediate layer between the user, the robot and the work piece and potentially leads to a decrease in productivity. Finally, the fear of the worker of being replaced by an improved robotic system was regularly expressed and adds an additional anthropocentric dimension to the discussion of human-robot cooperation, smart factories and the upcoming Industry 4.0.

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Section: Human-robot Interaction In the Industrial Environmentmentioning

confidence: 99%

Section: User-centered Development and Evaluationmentioning

confidence: 99%

First Application of Robot Teaching in an Existing Industry 4.0 Environment: Does It Really Work?

et al. 2016

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“…In qualitative analysis for collaboration task identification, the possible collaboration solution for each task is identified based on the comparison of the strength of human operator and robot manipulator with respect to performance requirements. Together with the definitions by Helms et al on four types of human-robot cooperation in industrial environment: independent operation, synchronized cooperation, simultaneous cooperation, and assisted cooperation (Helms et al, 2002), the collaboration tasks are identified and summarized in Table 2 for the first hierarchical level assembly tasks in cable harness assembly. The objective of Task 1, 'Prepare parts kit' (Super-ordinate 1) is to gather and arrange the assembly components into parts kit.…”

Section: Collaboration Analysismentioning

confidence: 99%

Collaboration Planning by Task Analysis in Human-Robot Collaborative Manufacturing System

Tan¹,

Duan²,

Kato³

et al. 2010

Advances in Robot Manipulators

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“…Some of these tasks require the precision and speed of automation, while others benefit from the dexterity and intelligence of human operators." HumanRobot Collaboration (HRC) brings benefits to industrial applications in terms of speed, efficiency, better quality of the production and better quality of the workplace (ergonomic) [2]. As far as now, robotic automation was seldom applied in small batch productions because of the variety of products and of variable production schedules [3].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Task Sharing Strategy for Adaptive Human-Robot Collaborative Workcell

Antonelli¹,

Bruno²

2018

dtetr

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Industry 4.0 prompts the re-organization of production systems with flexible collaborative workcells. Half way between the manual and the full automated cell, the new cell is configured by having humans and robots working together and collaborating to the execution of complex working tasks. Considering the production process subdivided in work tasks, it is apparent that some tasks could be performed more proficiently by humans or robots alone, others collaboratively. Analogy can be found with the job assignment problem in conventional production, for which a wide range of strategies and procedures has been researched. In Human-Robot Collaboration the procedures should be redefined having new objectives and following different rules. This is the intent of the study: to classify which tasks should be executed by men, robots or by both collaboratively. The classification method makes use of a training set of pre-classified tasks. Then task assignment combined with job scheduling is introduced to avoid resource overload.

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rob@work: Robot assistant in industrial environments

Cited by 126 publications

References 2 publications

First Application of Robot Teaching in an Existing Industry 4.0 Environment: Does It Really Work?

First Application of Robot Teaching in an Existing Industry 4.0 Environment: Does It Really Work?

Collaboration Planning by Task Analysis in Human-Robot Collaborative Manufacturing System

Dynamic Task Sharing Strategy for Adaptive Human-Robot Collaborative Workcell

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