Pneumatic Bionic Hand with Rigid-Flexible Coupling Structure

Chen, Chang; Sun, Jiteng; Wang, Long; Chen, Guojin; Xu, Ming; Ni, Jian; Ramli, Rizauddin; Su, Shaohui; Chu, Changyong

doi:10.3390/ma15041358

Cited by 9 publications

(3 citation statements)

References 25 publications

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“…This constraint directly impacts their carrying capacity, narrowing the spectrum of objects they can effectively grasp and thereby curtailing their application breadth. To address this, the integration of variable stiffness elements into soft hand systems has been proposed [94,95]. Activating these elements increases the structural stiffness of the gripper, aiding in the lifting of heavier loads.…”

Section: Methods To Enhance Grasping and Manipulation Performancementioning

confidence: 99%

Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Wang,

Hao,

Liu

et al. 2024

Actuators

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Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.

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Section: Methods To Enhance Grasping and Manipulation Performancementioning

confidence: 99%

Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Wang,

Hao,

Liu

et al. 2024

Actuators

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“…The bending deformation of the soft drive is closely related to the thickness of the bottom sealing layer. The common FPN actuator will embed a limiting strain layer at the bottom, which can limit the radial deformation of the bottom (Chen et al , 2022). The bottom sealing layer designed in this paper limits the radial deformation by increasing the thickness.…”

Section: Simulation Analysismentioning

confidence: 99%

Adaptive pneumatic soft gripper with embedded flexible bending sensor

Chen,

Liang,

Sun

et al. 2024

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Purpose The purpose of this paper is to introduce a variable distance pneumatic gripper with embedded flexible sensors, which can effectively grasp fragile and flexible objects. Design/methodology/approach Based on the motion principle of the three-jaw chuck and the pneumatic “fast pneumatic network” (FPN), a variable distance pneumatic holder embedded with a flexible sensor is designed. A structural design plan and preparation process of a soft driver is proposed, using carbon nanotubes as filler in a polyurethane (PU) sponge. A flexible bending sensor based on carbon nanotube materials was produced. A static model of the soft driver cavity was established, and a bending simulation was performed. Based on the designed variable distance soft pneumatic gripper, a real-time monitoring and control system was developed. Combined with the developed pneumatic control system, gripping experiments on objects of different shapes and easily deformable and fragile objects were conducted. Findings In this paper, a variable-distance pneumatic gripper embedded with a flexible sensor was designed, and a control system for real-time monitoring and multi-terminal input was developed. Combined with the developed pneumatic control system, a measure was carried out to measure the relationship between the bending angle, output force and air pressure of the soft driver. Flexible bending sensor performance test. The gripper diameter and gripping weight were tested, and the maximum gripping diameter was determined to be 182 mm, the maximum gripping weight was approximately 900 g and the average measurement error of the bending sensor was 5.91%. Objects of different shapes and easily deformable and fragile objects were tested. Originality/value Based on the motion principle of the three-jaw chuck and the pneumatic FPN, a variable distance pneumatic gripper with embedded flexible sensors is proposed by using the method of layered and step-by-step preparation. The authors studied the gripper structure design, simulation analysis, prototype preparation, control system construction and experimental testing. The results show that the designed flexible pneumatic gripper with variable distance can grasp common objects.

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“…The measurements of the forces generated in the joints are important data for many applications: the understanding of pathologies; the optimisation of treatments, for example, for ageing [2]; the design of ortheses and prostheses; the reproduction of movements or the understanding of gestures; the impact on blood circulation [3]; the creation of bionic hands [4], or the development of an exoskeleton [5]. The knowledge of the moment in the joint is the first step towards the estimation of the tensions on the tendons that cross this joint.…”

Section: Introductionmentioning

confidence: 99%

Development and Operation of an Experimental System to Measure the Moments Generated in the Finger Joints

et al. 2022

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Little information is available on the forces that fingers can generate, and few devices exist to measure the forces they can create. The objective of this paper is to propose an experimental device to measure the moments generated by finger joints. The idea is to focus on a single joint and not on the effort generated by the whole finger. A system leaving only one joint free is developed to measure the maximum attainable moment in different joint positions between the extended and flexed finger. The device is tested on the proximal interphalangeal joints of the index fingers of thirty people for both hands. The results show a dispersion of results from one person to another but with similar trends in the evolution of the maximum achievable moment depending on the angle. Average values of the maximum moments attained by men and women for both hands are given for all angular positions of the joint. The results are analysed using principal component analysis. This analysis shows that four main modes represent more than 99% of the signal and allow the reconstruction of all the data for all the subjects. The four modes obtained can be used as a basis for the development of finger devices by hospital practitioners.

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Pneumatic Bionic Hand with Rigid-Flexible Coupling Structure

Cited by 9 publications

References 25 publications

Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Adaptive pneumatic soft gripper with embedded flexible bending sensor

Development and Operation of an Experimental System to Measure the Moments Generated in the Finger Joints

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