Innovative control of assembly systems and lines

Krüger, Jörg; Wang, Lihui; Verl, Alexander; Bauernhansl, Thomas; Carpanzano, Emanuele; Makris, Sotiris; Fleischer, Jürgen; Reinhart, Gunther; Franke, Jöerg; Pellegrinelli, Stefania

doi:10.1016/j.cirp.2017.05.010

Cited by 88 publications

(25 citation statements)

References 115 publications

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“…Lightweight collaborative robots, such as those that have come to the market for assembly applications in recent years [110], allow human haptic guidance [82,35], in particular, to enable intuitive and efficient teach-in of individual poses or playback of movement profiles. Due to the low load-bearing capacity, they are not intended to relieve the physical burden on humans in the context of collaborative task execution [219].…”

Section:  Motion Control: the Robot Movements Occur Simultaneouslymentioning

confidence: 99%

Symbiotic human-robot collaborative assembly

et al. 2019

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In human-robot collaborative assembly, robots are often required to dynamically change their pre-planned tasks to collaborate with human operators in a shared workspace. However, the robots used today are controlled by pre-generated rigid codes that cannot support effective human-robot collaboration. In response to this need, multi-modal yet symbiotic communication and control methods have been a focus in recent years. These methods include voice processing, gesture recognition, haptic interaction, and brainwave perception. Deep learning is used for classification, recognition and context awareness identification. Within this context, this keynote provides an overview of symbiotic human-robot collaborative assembly and highlights future research directions.

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Section:  Motion Control: the Robot Movements Occur Simultaneouslymentioning

confidence: 99%

Symbiotic human-robot collaborative assembly

et al. 2019

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“…The increased demand for higher product variety as well as the evolution of manufacturing processes and control systems [4] has favoured the development of robotic applications that can undertake several tasks in the manufacturing chain either as standalone or as cooperating units [5,6]. The sorting and feeding of the parts are indicative examples.…”

Section: Introductionmentioning

confidence: 99%

A novel pneumatic gripper for in-hand manipulation and feeding of lightweight complex parts—a consumer goods case study

Michalos

Dimoulas

Mparis

et al. 2018

Int J Adv Manuf Technol

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This paper discusses the design and implementation of a robotic gripper that uses compressed air to (a) orient the parts in the desired grasping position, (b) guide the parts inside a grasping mechanism and (c) feed the parts to a track conveyor with sufficient accuracy. The novelty of the approach lays in the ability to perform in-hand manipulation of the object by the gripper allowing to pick randomly placed objects that have a complex geometry. Unlike existing 'pick and place' operations which are mainly focused on flat objects that require minimal manipulation (rotation around vertical axis), the gripper can re-orient the parts itself, minimizing the robot's motion. The major components of the gripper are 3D printed, allowing fast customization for different products. The manipulation and gripping mechanisms have been inspired by an application in the consumer goods industry involving the feeding of shaver handles to an assembly machine. The findings indicate that the proposed solution can be an alternative to part-dedicated, high-cost feeding equipment that is currently used.

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“…Moreover, in CaaS, a variety of control algorithms could be offered in an "app marketplace", where they are accessed if and when needed by a given device. For more details on the various benefits of CaaS, see [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…The solutions to QoS issues presented in the discussed preliminary studies have yielded encouraging results: they have generally demonstrated that, with proper mitigation of QoS issues, cloud-based controllers can approach the performance of equivalent local controllers. However, the aspiration of CaaS is for cloud-based controllers to surpass the Cloud-based control in the context of CaaS seeks to perform low-level computations for real-time control of a device in the Cloud, instead of on a local controller [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. In the specific case of 3D printers, this implies that stepper motor commands (or similar low-level signals) are computed in and sent out from the cloud-based controller, as opposed to G-codes (see Figure 1b).…”

Section: Introductionmentioning

confidence: 99%

Low-Level Control of 3D Printers from the Cloud: A Step toward 3D Printer Control as a Service

et al. 2018

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Control as a Service (CaaS) is an emerging paradigm where low-level control of a device is moved from a local controller to the Cloud, and provided to the device as an on-demand service. Among its many benefits, CaaS gives the device access to advanced control algorithms which may not be executable on a local controller due to computational limitations. As a step toward 3D printer CaaS, this paper demonstrates the control of a 3D printer by streaming low-level stepper motor commands (as opposed to high-level G-codes) directly from the Cloud to the printer. The printer is located at the University of Michigan, Ann Arbor, while its stepper motor commands are calculated using an advanced motion control algorithm running on Google Cloud computers in South Carolina and Australia. The stepper motor commands are sent over the internet using the user datagram protocol (UDP) and buffered to mitigate transmission delays; checks are included to ensure accuracy and completeness of the transmitted data. All but one part printed using the cloud-based controller in both locations were hitch free (i.e., no pauses due to excessive transmission delays). Moreover, using the cloud-based controller, the parts printed up to 54% faster than using a standard local controller, without loss of accuracy.

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Innovative control of assembly systems and lines

Cited by 88 publications

References 115 publications

Symbiotic human-robot collaborative assembly

Symbiotic human-robot collaborative assembly

A novel pneumatic gripper for in-hand manipulation and feeding of lightweight complex parts—a consumer goods case study

Low-Level Control of 3D Printers from the Cloud: A Step toward 3D Printer Control as a Service

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