From Visual Understanding to Complex Object Manipulation

Bütepage, Judith; Cruciani, Silvia; Kokić, Mia; Welle, Michael C.; Kragić, Danica

doi:10.1146/annurev-control-053018-023735

Cited by 13 publications

(7 citation statements)

References 70 publications

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“…Seperti kegiatan memotong, menyekop, menyendok, mengaduk dan sebagainya (Gajewski et al, 2019). Semakin baik keterampilan manipulasi seseorang, membuat mereka mampu merancang robot yang dapat mempermudah pekerjaan manusia (Bütepage et al, 2019;Erlianda et al, 2019;Kim et al, 2021). Memandang hal ini sekolah memiliki peran besar dalam menstimulasi keterampilan manipulasi anak (Eddy, LH, Wood, ML, Shire, 2019).…”

Section: Bagan 3 Implementation Of Systematic Reviewunclassified

Keterampilan Penting Sebelum Anak Siap Menulis

Andika

Utami

Sumarni

et al. 2022

J. Obs. J. Pendidik. Anak Usia Dini

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Adanya kesenjangan antara orang tua yang menginginkan anaknya segera terampil menulis dan fakta bahwa anak memerlukan kesiapan fisik yang matang dalam menulis. Kesenjangan tersebut menimbulkan pertanyaan apa saja keterampilan yang penting distimulasi sebelum anak siap menulis. Tujuan penelitian ini mengkaji literatur hasil penelitian tentang keterampilan sebelum anak siap menulis. Metode penelitian adalah studi literatur dari sumber primer. Hasil kajian literatur menyatakan terdapat: kekuatan otot inti, menyilangkan garis tengah, menggenggam pensil dengan benar, koordinasi mata-tangan, integrasi bilateral, kekuatan tubuh bagian atas, manipulasi objek, persepsi visual, dominasi tangan visual. Kebaharuan penelitian ini mengkaji informasi tentang sembilan keterampilan yang harus distimulasi sebelum anak siap menulis dari 45 hasil penelitian terbaru. Dampaknya guru dapat memfokuskan pengembangan keterampilan tersebut secara optimal sehingga anak tidak mudah letih saat menulis dan anak dapat menggunakan keterampilan pada aktivitas lebih kompleks. Simpulan pentingnya stimulasi keterampilan tersebut sebagai indikator kesiapan menulis anak.

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Section: Bagan 3 Implementation Of Systematic Reviewunclassified

Keterampilan Penting Sebelum Anak Siap Menulis

Andika

Utami

Sumarni

et al. 2022

J. Obs. J. Pendidik. Anak Usia Dini

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“…Grasping and manipulation of rigid objects have been studied extensively. [1][2][3][4] In contrast, deformable object manipulation received relatively little attention due to the challenges related to the complexity in modeling, tracking and control. 5 Manipulating clothing items is particularly difficult, as classical control approaches that require modeling the objects' dynamics are only applicable in restrictive settings.…”

Section: Introductionmentioning

confidence: 99%

Cloth manipulation based on category classification and landmark detection

Gustavsson

Ziegler

Welle

et al. 2022

International Journal of Advanced Robotic Systems

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Cloth manipulation remains a challenging problem for the robotic community. Recently, there has been an increased interest in applying deep learning techniques to problems in the fashion industry. As a result, large annotated data sets for cloth category classification and landmark detection were created. In this work, we leverage these advances in deep learning to perform cloth manipulation. We propose a full cloth manipulation framework that, performs category classification and landmark detection based on an image of a garment, followed by a manipulation strategy. The process is performed iteratively to achieve a stretching task where the goal is to bring a crumbled cloth into a stretched out position. We extensively evaluate our learning pipeline and show a detailed evaluation of our framework on different types of garments in a total of 140 recorded and available experiments. Finally, we demonstrate the benefits of training a network on augmented fashion data over using a small robotic-specific data set.

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“…Manipulation is one of the most common actions for robots to physically interact with the world. As we see an increasing amount of real-world applications being deployed in recent years, robotic manipulation is still a challenging problem that involves many subproblems yet to be addressed, such as complex system dynamics, multimodal sensing, planning and control, and hardware design, particularly for manipulation in unstructured environments (1)(2)(3). For grasp-based manipulation, numerous tasks can be achieved purely through arm motions, such as the most common pick-and-place tasks.…”

Section: Introductionmentioning

confidence: 99%

Manipulation for self-Identification, and self-Identification for better manipulation

et al. 2021

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The process of modeling a series of hand-object parameters is crucial for precise and controllable robotic in-hand manipulation because it enables the mapping from the hand’s actuation input to the object’s motion to be obtained. Without assuming that most of these model parameters are known a priori or can be easily estimated by sensors, we focus on equipping robots with the ability to actively self-identify necessary model parameters using minimal sensing. Here, we derive algorithms, on the basis of the concept of virtual linkage-based representations (VLRs), to self-identify the underlying mechanics of hand-object systems via exploratory manipulation actions and probabilistic reasoning and, in turn, show that the self-identified VLR can enable the control of precise in-hand manipulation. To validate our framework, we instantiated the proposed system on a Yale Model O hand without joint encoders or tactile sensors. The passive adaptability of the underactuated hand greatly facilitates the self-identification process, because they naturally secure stable hand-object interactions during random exploration. Relying solely on an in-hand camera, our system can effectively self-identify the VLRs, even when some fingers are replaced with novel designs. In addition, we show in-hand manipulation applications of handwriting, marble maze playing, and cup stacking to demonstrate the effectiveness of the VLR in precise in-hand manipulation control.

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From Visual Understanding to Complex Object Manipulation

Cited by 13 publications

References 70 publications

Keterampilan Penting Sebelum Anak Siap Menulis

Keterampilan Penting Sebelum Anak Siap Menulis

Cloth manipulation based on category classification and landmark detection

Manipulation for self-Identification, and self-Identification for better manipulation

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