Design and Fuzzy Control of a Pneumatic Advanced Gripper

Mattiazzo, Giuliana; Mauro, Stefano; Velardocchia, Mauro; Raparelli, Terenziano

doi:10.1080/10798587.1998.10750742

Cited by 5 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Each finger of the NTU hand having six inputs (three joint positions and three force functions) and three outputs (received from the analog controller). Mattiazzo et al 32 developed a three-finger pneumatic gripper robotic gripper, which is controlled by the fuzzy controller. A five-finger pneumatic anthropometric robotic hand was developed.…”

Section: Application Of Soft Computing Techniques In Robotic Graspingmentioning

confidence: 99%

Application of soft computing methods in robotic grasping: A state-of-the-art survey

Mahanta

Deepak²,

Biswal³

2021

Proceedings of the Institution of Mechanical Engineers, Part E:

View full text Add to dashboard Cite

Robotic grasping has become one of the most important domains of robotics research over the past few decades due to its wide range of applications in industrial automation. The model of grasping objects by robot hand depends on a good number of factors, such as type and size of the object, the morphology of object, type of hand, degree of freedom, etc. Thus, the model sometimes becomes mathematically intractable. With the progress in computational capability, soft computing methods have found a way to address the challenges faced by traditional methods while dealing with the robotic grasping problem. This article aims to summarize the outcome of a systematic study in the field of application of soft computing methods in robotic grasping and manipulation. The key processes of robotic grasping where soft computing methods are applied are identified, and research contributions of all processes are analyzed. This review presents a state-of-the-art survey and attempts to find the research gaps in the area of soft computing applications to address the robotic grasping problem.

show abstract

Section: Application Of Soft Computing Techniques In Robotic Graspingmentioning

confidence: 99%

Application of soft computing methods in robotic grasping: A state-of-the-art survey

Mahanta

Deepak²,

Biswal³

2021

Proceedings of the Institution of Mechanical Engineers, Part E:

View full text Add to dashboard Cite

show abstract

“…The hand described in this work is a development of an advanced gripper previously developed by the same authors. 23 In this former work two pneumatically actuated articulated fingers were assembled with a mobile palm to develop a device for grasping slender objects. The up-to-date hand is composed of four fingers of the same type and an opposable thumb, which was previously studied as a stand-alone device.…”

Section: Introductionmentioning

confidence: 99%

Design and development of a pneumatic anthropomorphic hand

Raparelli¹,

Mattiazzo²,

Mauro³

et al. 2000

J. Robotic Syst.

Self Cite

View full text Add to dashboard Cite

This work deals with a pneumatically actuated hand composed of four fingers and an opposable thumb. Mechanisms to convert actuator motion into phalanx rotation were studied to make each finger as similar as possible to the human specimen. Force tactile sensors are disposed along the phalanxes to allow a closed-loop force control, while the thumb position is sensorized by a potentiometer and hence position controlled. Each component is controlled by fuzzy logic. This solution allowed the existing strong nonlinearities to be easily managed. A fuzzy supervisor applies a grasping strategy whose target is an approximate identification of the shape and size of an object to grasp it most efficiently with the disposable fingers.

show abstract

Dynamic Control of a Large Scale of Pneumatic Multichain Systems

Guihard

Gorce

2004

J. Robotic Syst.

View full text Add to dashboard Cite

The aim of this paper is to propose a general principle able to manage the supervision, coordination, and control problems of a large scale of multichain structures in dynamic and interacting tasks. The main originality lays in its modular feature. The number of chains and of joint per chain are indeed not restricted. The only assumption is that all the chains are linked to a principal element from which the dynamic stability will be computed. This is for example the case for multi‐finger and multi‐legged structures for which respectively the palm and the trunk represent the principal element. The principle consists in controlling the stability of this element and distributing the effort on the other chains to maintain the stability of the whole. To increase the compliant feature, we consider that each joint is pneumatically actuated. Each joint is then dynamically controlled to ensure the asymptotic stability of the local chain it belongs to. A global architecture is presented where each part is detailed. An example is then displayed showing the performances of a two‐legged robot in the standing posture under external perturbation effects. © 2004 Wiley Periodicals, Inc.

show abstract

Design and Fuzzy Control of a Pneumatic Advanced Gripper

Cited by 5 publications

References 8 publications

Application of soft computing methods in robotic grasping: A state-of-the-art survey

Application of soft computing methods in robotic grasping: A state-of-the-art survey

Design and development of a pneumatic anthropomorphic hand

Dynamic Control of a Large Scale of Pneumatic Multichain Systems

Contact Info

Product

Resources

About