Structured collaborative behavior of industrial robots in mixed human-robot environments

Ding, Hu; Heyn, Jakob; Matthias, Björn; Staab, Harald

doi:10.1109/coase.2013.6653962

Cited by 20 publications

(13 citation statements)

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“…Preliminary versions of these ideas have been originally reported in [26] and [27]. The present paper extends the previous work by fully exploiting the methodology in case of redundant degrees of freedom and presents new and more involved case studies.…”

mentioning

confidence: 73%

“…The first part discusses the data flow within the proposed control scheme, whilst a higher level picture of the control architecture is given later on in this section. A preliminary sketch of the control architecture can be found in [27].…”

Section: Overall Control Architecturementioning

confidence: 99%

“…In order to sketch an overall picture of the control architecture, we here exploit and complement some previously developed concepts, see, e.g., [23] and [27]. The state machine in Fig.…”

Section: B Supervision and State Machinesmentioning

confidence: 99%

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Safety in human-robot collaborative manufacturing environments: Metrics and control

Zanchettin

Ceriani

Rocco

et al. 2016

IEEE Trans. Automat. Sci. Eng.

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316

174

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Twenty years ago, the field of Robotics was defined and galvanized by the creation of an IEEE Journal devoted to the topic. We now have the opportunity to do the same for the field of Automation. The IEEE voted in February 2003 to bifurcate the IEEE Transactions on Robotics and Automation, the top-cited archival publication on robotics. The renamed Transactions on Robotics will gain a sibling: the Transactions on Automation Science and Engineering.T-ASE will publish foundational research on Automation: scientific methods and technologies that improve efficiency, productivity, quality, and reliability, specifically for methods, machines, and systems operating in structured environments over long periods, and the explicit structuring of environments. Its coverage will go beyond Automation's roots in mass production and include many new applications areas, such as Biotechnology, pharmaceutical, and health care; Home, service, and retail; Construction, transportation, and security; Manufacturing, maintenance, and supply chains; and Food handling and processing. Research includes topics related to robots and intelligent machines/systems in structured environments and the explicit structuring of environments, and topics at the Operational/Enterprise levels such as System Modeling, Analysis, Performance Evaluation; Planning, Scheduling, Coordination; Risk Management; and Supply Chain Management. T-ASE will integrate knowledge across disciplines and industries.Details on IEEE's motivation, distinctions between Robotics and Automation, scope statements, and sample application areas are available at: http://www.ieee.org/t-ase. The first issue will appear in July 2004.Paper Categories: T-ASE publishes both Regular and Short Papers and Communication Items. Regular papers describe new abstractions, algorithms, theory, methodologies, models, systems, or enabling technologies for Automation. Short papers usually describe a single result, experiment, or technique of general interest for which a short treatment is appropriate. Communications items are a separate class of short manuscripts that are subject to an expedited review process and substantially faster publication than regular or short papers. Appropriate items include (but are not limited to) rebuttals and/or counter examples of previously published papers, or preliminary results of significant current research of wide interest. Review papers are published periodically, and manuscripts of a tutorial or review nature are welcome. Papers describing specific current applications are encouraged, provided that the methods represent the best current practice, detailed characteristics and performance are included, and they are of general interest. Multipart papers will only be published if there is compelling rationale for a multipart treatment. All parts of such submissions must be accepted for any part to be published. In addition, T-ASE addresses a research community willing to integrate knowledge across disciplines and industries. For this purpose, each paper shall includ...

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confidence: 73%

Section: Overall Control Architecturementioning

confidence: 99%

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Safety in human-robot collaborative manufacturing environments: Metrics and control

Zanchettin

Ceriani

Rocco

et al. 2016

IEEE Trans. Automat. Sci. Eng.

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316

174

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“…In every case, the speed is reduced if the worker approaches further to the concept robot. The collaborative behavior design of the robot interacting with multiple human is described in [7] [8].…”

Section: A Setup Of the Assembly Stationmentioning

confidence: 99%

Optimized task distribution for industrial assembly in mixed human-robot environments - Case study on IO module assembly

Ding¹,

Schipper²,

Matthias³

2014

2014 IEEE International Conference on Automation Science and Engineering (CASE)

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Introduction of robots into manual assembly lines to assist human workers or introduction of human into robot-based manufacturing attracts more and more attention in academy and industry. This interest stems from the insight that the integration of robots into manual assembly lines or vice versa may increase productivity by combining the abilities of machines with those of humans. To uphold productivity while respecting safety constraints is the target, and one of the challenges is how to productively distribute tasks among workers and robots. We studied one small-part assembly scenario, namely the assembly of a PLC Input/Output module by an ABB Dual Arm Concept Robot and a human worker. A method is proposed in this paper to optimize the operation/task assignment in the collaborative environment. An exemplary calculation shows that the cycle time can be shortened to increase the productivity. Finally, we show that the developed method can also be generalized and applied to different scenarios in mixed environments.

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“…Within this period, Executive Summary Word Robotics also predicts that human-robot collaboration will have a breakthrough due in part because compact and easy-to-use CoBots will drive the market (Executive Summary World Robotics, 2016). With CoBots expected impact on productivity and workers' safety (Ding et al, 2013;Akella et al, 1999), it is imperative that higher education institutions incorporate this technology into learning programs for a career-ready workforce. This paper describes an advanced, industry-driven, hands-on learning environment and educational curriculum focused on collaborative robotics and the integration of the technology into advanced manufacturing systems.…”

Section: Introductionmentioning

confidence: 99%

Hands-on Learning Environment and Educational Curriculum on Collaborative Robotics

Djuric¹,

Rickli²,

Jovanović³

et al.

2017 ASEE Annual Conference &Amp; Exposition Proceedings

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he has created the Manufacturing and Remanufacturing Systems Laboratory (MaRSLab). MaRSLab targets fundamental and applied research in manufacturing and remanufacturing processes and systems while encouraging considerations for sustainability and life-cycle thinking in design, manufacturing, use, and recovery. Specific research thrusts include: transforming manufacturing quality monitoring and remanufacturing core condition assessment via automated laser line scanning systems; remanufacturing core management considering uncertain core quality, quantity, and timing; and integrating design for disassembly and remanufacturing into CAD/CAM tools. He has collaborated in the past with industrial partners on projects involving residual stresses in lightweight aluminum alloy side rails, manufacturing process simulation, and enhancing end-of-life truck acquisition decisions. Dr. Rickli is also actively involved in outreach activities with Athletes for Charity STEM Youth Literacy Program, which provides Detroit Public Schools with STEM educational sessions. Dr. Foster worked on numerous welding and additive manufacturing projects funded by the National Science Foundation, The Ohio State University, and Ohio Space Grant Consortium fellowships. His current research is funded by the National Shipbuilding Research Program, the National Science Foundation, and the Virginia Space Grant Consortium. In addition, Dr. Foster also has had the honor of serving as a Faculty Fellow at NASA's Glen Research Center.Dr. Foster's research focuses on advanced materials joining and additive manufacturing, with particular expertise in in-situ process monitoring. A current research effort of his includes Improving Technical Welding Education Using Real-Time Sensory Feedback, where his lab is developing and testing the realtime feedback of manual welding to increase efficiency and cost-savings during welding training. Other topics of his is Process Monitoring of Ultrasonic Additive Manufacturing and Ultrasonic Welding. Future work includes linking in-situ data to process maps, creating a closed loop process monitoring system that can automatically adjust process parameters in real-time to ensure superior part quality.c American Society for Engineering Education, 2017 Hands-on Learning Environment and Educational Curriculum on Collaborative Robotics AbstractThe objective of this paper is to describe teaching modules developed at Wayne State University integrate collaborative robots into existing industrial automation curricula. This is in alignment with Oakland Community College and WSU's desire to create the first industry-relevant learning program for the use of emerging collaborative robotics technology in advanced manufacturing systems. The various learning program components will prepare a career-ready workforce, train industry professionals, and educate academicians on new technologies. Preparing future engineers to work in highly automated production, requires proper education and training in CoBot theory and applications. Engineering and ...

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Structured collaborative behavior of industrial robots in mixed human-robot environments

Cited by 20 publications

References 14 publications

Safety in human-robot collaborative manufacturing environments: Metrics and control

Safety in human-robot collaborative manufacturing environments: Metrics and control

Optimized task distribution for industrial assembly in mixed human-robot environments - Case study on IO module assembly

Hands-on Learning Environment and Educational Curriculum on Collaborative Robotics

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