A versatile end effector for grabbing and spreading of flaky deformable object manipulation

Yuan, Huatang; Ren, Ge; Su, Xiangyu; Tian, Wei

doi:10.5194/ms-14-111-2023

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…To validate the effectiveness of the dual-arm grasping and spreading strategy and the identification algorithm, an experimental platform is constructed using two AUBO-i5 robotic arms with wheeled end-effectors 24 , Intel RealSense D435i depth camera, light source, a work platform, and a supervisory computer, as shown in Fig. 10 .…”

Section: Grasping and Spreading Experimentsmentioning

confidence: 99%

Efficient leather spreading operations by dual-arm robotic systems

Huan,

Ren,

Sun

et al. 2024

Sci Rep

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To achieve precise grasping and spreading of irregular sheet-like soft objects (such as leather) by robots, this study addresses several challenges, including the irregularity of leather edges and the ambiguity of feature recognition points. To tackle these issues, this paper proposes an innovative method that involves alternately grasping the lowest point twice and using planar techniques to effectively spread the leather. We improved the YOLOV8 algorithm by incorporating the BIFPN network structure and the WIOU loss function, and trained a dedicated dataset for the lowest grasping points and planar grasping points, thereby achieving high-precision recognition. Additionally, we determined the optimal posture for grasping the lowest point and constructed an experimental platform, successfully conducting multiple rounds of leather grasping and spreading experiments with a success rate of 72%. Through an in-depth analysis of the failed experiments, this study reveals the limitations of the current methods and provides valuable guidance for future research.

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Section: Grasping and Spreading Experimentsmentioning

confidence: 99%

Efficient leather spreading operations by dual-arm robotic systems

Huan,

Ren,

Sun

et al. 2024

Sci Rep

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“…Donaire et al 1 engineered a multifunctional gripper for fabric manipulation, which, aside from thumb and index finger pinching capability, boasts two reconfigurable degrees of freedom that enable the dexterous pick-up, placement, and folding of garments through thumb cooperation with the other two fingers. Huan et al 5 achieved versatile manipulation of non-uniform flaky deformation objects through an end-effector designed with reconfigurable multi-linkages and dual roller fingertips.…”

mentioning

confidence: 99%

“…Similarly, Yamazaki and Abe 10 were involved in the design of a roller manipulator, proposing a novel operational approach and subsequently executing a series of grasping experiments. Among the plethora of robotic hands engineered, the model employed by Huan et al 5 and Yamazaki and Abe, 10 which utilizes two cooperating roller fingertips, is representative. As the process of roller-type robotic hands grasping sheet-like soft objects differs from that of three-fingered and soft robotic hands, with more complex influencing factors and mechanisms, the extant literature primarily focuses on conducting grasping experiments or elucidating various factors influencing the grasping process, yet it lacks a holistic analysis and exploration.…”

mentioning

confidence: 99%

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Analysis and experimental investigation of the factors influencing the grasping of planar flaky deformation objects in a laid-out configuration

Huan,

Ren,

et al. 2024

Textile Research Journal

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This study endeavors to elucidate the salient factors that influence the efficacy of roller-based robotic manipulators in grasping multi-layered flaky deformation objects in a planar configuration. Through a rigorous force analysis of the grasping process, it was ascertained that the manipulation of flaky deformation objects is influenced by four forces. Subsequent analysis of the genesis of these forces enabled the identification of four pivotal factors: the applied downward pressure, the location of grasp, the number of stacked layers, and the coefficient of friction. To gain a comprehensive understanding of how these factors dictate the grasping efficacy, a series of meticulously designed experiments was conducted. The findings reveal that augmenting the coefficient of friction between the roller and fabric, intensifying the downward pressure, increasing the number of stacked layers, and opting for a grasp location proximal to the edge significantly bolster the success rate of grasping. These revelations hold the potential to furnish theoretical guidance for optimizing the grasping strategies of roller-based robotic manipulators under practical operational conditions.

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Combining finite element analysis and reinforcement learning for optimal grip point planning of flexible components

Römer,

Demircan,

Hürkamp

et al. 2024

Prod. Eng. Res. Devel.

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Handling large flexible components is still a challenge in many industries. Examples include the handling of fibre-reinforced plastics or the assembly of industrial-scale electrolytic cells. Difficulties often arise in the design of suitable endeffectors. Inefficient gripping point design, i.e. the total number and positioning of grippers, can lead to increased stress and deflection of the component being handled. To counteract this, endeffectors are often oversized resulting in the use of more grippers than needed. Correspondingly, heavier moving masses imply longer handling times as well as higher energy consumption. This paper presents a process for planning and optimising gripping points for large flexible components. In addition to the shape of the component, actual dynamic loads of the handling path are also taken into account. The key element to the process is an optimisation algorithm based on reinforcement learning and trained using an finite element method (FEM) simulation. After computing a desirable starting configuration, the algorithm optimises the placement of gripper positions while aiming for a reduced total number. In addition, the optimisation has prescribed handling limits, such as physical and geometric constraints, that must not be exceeded. It was shown that the algorithm satisfactorily optimises the gripping points for dynamic loads for different materials and shapes. Furthermore, it has been shown that the computation of an initial configuration yields preferable results for simple components, yet requiring optimisation in the case of more complex shapes.

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A versatile end effector for grabbing and spreading of flaky deformable object manipulation

Cited by 5 publications

References 18 publications

Efficient leather spreading operations by dual-arm robotic systems

Efficient leather spreading operations by dual-arm robotic systems

Analysis and experimental investigation of the factors influencing the grasping of planar flaky deformation objects in a laid-out configuration

Combining finite element analysis and reinforcement learning for optimal grip point planning of flexible components

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