Finger design automation for industrial robot grippers: A review

Honarpardaz, Mohammadali; Tarkian, Mehdi; Ölvander, Johan; Feng, Xiaolong

doi:10.1016/j.robot.2016.10.003

Cited by 87 publications

(46 citation statements)

References 65 publications

(119 reference statements)

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“…A large number of optimization schemes for the multifinger design have been discussed, which shows great promise to grip and manipulate objects of varying shapes (2,18). However, this active approach usually entails visual/force feedbacks; a central processor and complex algorithms to decide the gripping schemes (19)(20)(21) such as how wide the fingers should open and how much stress should be applied on the objects and where to apply it; and the complex design and integration of sensors, joints, and actuators (18,22). Besides, the multifinger gripper is incapable of dealing with thin and fragile objects (2).…”

Section: Introductionmentioning

confidence: 99%

Universal SMP gripper with massive and selective capabilities for multiscaled, arbitrarily shaped objects

et al. 2020

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Grippers are widely used for the gripping, manipulation, and assembly of objects with a wide range of scales, shapes, and quantities in research, industry, and our daily lives. A simple yet universal solution is very challenging. Here, we manage to address this challenge utilizing a simple shape memory polymer (SMP) block. The embedding of objects into the SMP enables the gripping while the shape recovery upon stimulation facilitates the releasing. Systematic studies show that friction, suction, and interlocking effects dominate the grip force individually or collectively. This universal SMP gripper design provides a versatile solution to grip and manipulate multiscaled (from centimeter scale down to 10-μm scale) 3D objects with arbitrary shapes, in individual, deterministic, or massive, selective ways. These extraordinary capabilities are demonstrated by the gripping and manipulation of macroscaled objects, mesoscaled steel sphere arrays and microparticles, and the selective and patterned transfer printing of micro light-emitting diodes.

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Section: Introductionmentioning

confidence: 99%

Universal SMP gripper with massive and selective capabilities for multiscaled, arbitrarily shaped objects

et al. 2020

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“…In [4], we have highlighted that the current approaches in the field of finger design research may be classified as modular design, re-configurable design and customized design. According to the conclusion, customized design Fast Grasp Tool Design: From Force to Form Closure * M. Honarpardaz, M. Meier, and R. Haschke method are the most suitable approach for finger design automation due to their genericity.…”

Section: B Finger Generationmentioning

confidence: 99%

“…In our earlier comprehensive review [4] in finger design automation research area, we have shown that the very few proposed methods suffer two significant problems. First, the methods that are unable to handle objects with complex geometry.…”

Section: Introductionmentioning

confidence: 99%

Fast grasp tool design: From force to form closure

Honarpardaz

Meier

Haschke

2017

2017 13th IEEE Conference on Automation Science and Engineering (CASE)

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Abstract-We present a novel technique which integrates automatic, part centered design of customized fingertips with a grasp planning stage for arbitrary parts of an assembly process. Starting with a set of CAD models of parts in an assembly sequence, force closure grasps are generated for each part in a sampling process. By employing the sampled force closure grasp positions in the second stage, the fingertip shape model is adapted to obtain form closure grasps at the specific grasp locations on the part. This approach significantly reduces the process time of designing fingers. Furthermore, the method increases the robustness of the fingers grasp for precise assemblies. The proposed fast generic automated finger design (FGAFD) method is able to design fingers for various geometrically complex workpieces. The designed fingers are experimentally verified. The results are discussed in detail and benchmarked against existing approaches.

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“…For all the progress that we have seen, however, (i) robotic platforms remain best at pre-sorted, pick-andplace assembly tasks [23]; and (ii) many prosthetic users still prefer simple designs like the revered whole-or split-hook designs originally developed centuries ago [24,25].…”

Section: Introductionmentioning

confidence: 99%

On neuromechanical approaches for the study of biological and robotic grasp and manipulation

Valero-Cuevas

Santello

2017

J NeuroEngineering Rehabil

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Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.

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Finger design automation for industrial robot grippers: A review

Cited by 87 publications

References 65 publications

Universal SMP gripper with massive and selective capabilities for multiscaled, arbitrarily shaped objects

Universal SMP gripper with massive and selective capabilities for multiscaled, arbitrarily shaped objects

Fast grasp tool design: From force to form closure

On neuromechanical approaches for the study of biological and robotic grasp and manipulation

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