Multi-arm robot control system for manipulation of flexible materials in sewing operation

Kudo, Makoto; Nasu, Yasuo; Mitobe, Kazuhisa; Borovać, Branislav

doi:10.1016/s0957-4158(99)00047-1

Cited by 41 publications

(19 citation statements)

References 10 publications

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“…In Kudo et al [KNMB00], a system based on two robots that cooperate to handle a single fabric similar to a human worker during the sewing operation is presented. The implementation includes controllers for tension control, control of the pressing force, and synchronization with the sewing machine speed.…”

Section: Related Workmentioning

confidence: 99%

Real-time analysis of a multi-robot sewing cell

Schrimpf

Lind

Mathisen

2013

2013 IEEE International Conference on Industrial Technology (ICIT)

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SummaryThis PhD thesis presents topics related to sensor-based real-time robot control in applied automation.While in the past industrial challenges often could be solved with traditional robot programming methods, the industry looks more and more towards the automation of complex tasks that need real-time sensor-feedback in the control loop of the robot. This is especially important in applications where the workpiece shape or characteristics are uncertain or unknown. When working on such workpieces, the movement has to be adjusted in real-time, ie. while the robot is moving. To achieve this, sensors are added in the control loop of the robot.One challenge for the implementation of industrial solutions including real-time control is the lack of appropriate interfaces in most commercially available robots. When such interfaces are not present, in-house developed solutions can be used to access the low-level system of the robots, at least for research applications. These usually require modifications of the hardware, the software platform or both. Often, interfaces are implemented that allows for parts of the control loop being moved to an external PC. In this thesis, real-time interfaces for two different industrial manipulators are presented that are used for lab experiments and demonstrators. The real-time interfaces work position-based and have update frequencies of about 100 Hz. Ethernet UDP is used to communicate with the external controller platform. Experiments are presented that measure the delays in the low-level systems of the robots.To externally control the movement of the real-time controlled robots from an application controller, a trajectory generator is needed. This thesis gives an overview of three different on-line trajectory generators that were in-house developed. The real-time capabilities of the presented trajectory generators were analyzed in order to ensure that the requirement for response times of the real-time interfaces are met.Based on a presented real-time interface and trajectory generator, a iii iv test platform was built. The test platform demonstrates tracking of a line that is sketched on the workpiece. The robot tool is controlled to keep a fixed distance between tool and workpiece, while maintaining an orientation perpendicular to the workpiece surface. The line tracking is done using a line-of-sight based control method. Experiments are presented, measuring the delays in the robot-sensor system. The main part of this thesis is a presentation of an automated robotic sewing cell that demonstrates a case of sewing for the furniture industry. The system is able to sew together two parts with slightly different shapes. A two-robot solution is presented that controls the work pieces independently during the sewing operation. A force sensor is integrated in the control system to keep a constant sewing force. The seam allowance is controlled by an edge control system based on optical sensors that are mounted on the sewing machine. The real-time capabilities of the system are analyze...

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Section: Related Workmentioning

confidence: 99%

Real-time analysis of a multi-robot sewing cell

Schrimpf

Lind

Mathisen

2013

2013 IEEE International Conference on Industrial Technology (ICIT)

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“…Relevant topics in this field include multi-arm robotic sewing [8], tension control for fabric, and edge tracking [9]. To cope with environmental changes during sewing, various control strategies have been implemented, such as fuzzy logic controllers [10], hybrid position/force control [8], and leader/follower control strategies [11]. Research has also been carried out on the redesign of sewing machines that are capable of sewing from a single side of the fabric and therefore facilitate sewing on complex 3D surfaces.…”

Section: Related Workmentioning

confidence: 99%

A Multirobot Cooperation Framework for Sewing Personalized Stent Grafts

Huang

et al. 2018

IEEE Trans. Ind. Inf.

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This paper presents a multi-robot system for manufacturing personalized medical stent grafts. The proposed system adopts a modular design, which includes: a (personalized) mandrel module, a bimanual sewing module, and a vision module. The mandrel module incorporates the personalized geometry of patients, while the bimanual sewing module adopts a learning-by-demonstration approach to transfer human hand-sewing skills to the robots. The human demonstrations were firstly observed by the vision module and then encoded using a statistical model to generate the reference motion trajectories. During autonomous robot sewing, the vision module plays the role of coordinating multirobot collaboration. Experiment results show that the robots can adapt to generalized stent designs. The proposed system can also be used for other manipulation tasks, especially for flexible production of customized products and where bimanual or multirobot cooperation is required.

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“…There are however few industrial cases of automated sewing, typically aided by special purpose customized fixtures. Automation of sewing processes has been investigated by some authors: Seliger and Stephan [215], Kudo et al [120], Wittig and Rattay [281], Wittig [280] and Kawauchi [113]. The problem is not only the sewing itself, but also the handling of materiel into and out of the sewing process.…”

Section: Sewing and Filament Windingmentioning

confidence: 99%