A study on fingertip designs and their influences on performing stable prehension for robot hands

Or, Keung; Morikuni, Shu; Ogasa, Shun; Funabashi, Satoshi; Schmitz, Alexander; Sugano, Shigeki

doi:10.1109/humanoids.2016.7803361

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Creating soft grasping devices has been an area of intense interest for many years, as the rigid graspers characteristic of most robots are unable to handle fragile, soft and crushable materials. Investigators have explored the use of robots with soft fingers (Arimoto et al, 2000; Li and Kao, 2001; Or et al, 2016). A recent study used a topology optimization approach and three-dimensional printing to create a two-‘finger’ soft gripper that could handle a variety of fragile objects of differing sizes (Liu et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Soft-surface grasping: radular opening in Aplysia californica

Kehl

et al. 2019

Journal of Experimental Biology

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Grasping soft, irregular material is challenging both for animals and robots. The feeding systems of many animals have adapted to this challenge. In particular, the feeding system of the marine mollusk Aplysia californica, a generalist herbivore, allows it to grasp and ingest seaweeds of varying shape, texture and toughness. On the surface of the grasper of A. californica is a structure known as the radula, a thin flexible cartilaginous sheet with fine teeth. Previous in vitro studies suggested that intrinsic muscles, I7, are responsible for opening the radula. Lesioning I7 in vivo does not prevent animals from grasping and ingesting food. New in vitro studies demonstrate that a set of fine muscle fibers on the ventral surface of the radula – the sub-radular fibers (SRFs) – mediate opening movements even if the I7 muscles are absent. Both in vitro and in vivo lesions demonstrate that removing the SRFs leads to profound deficits in radular opening, and significantly reduces feeding efficiency. A theoretical biomechanical analysis of the actions of the SRFs suggests that they induce the radular surface to open around a central crease in the radular surface and to arch the radular surface, allowing it to softly conform to irregular material. A three-dimensional model of the radular surface, based on in vivo observations and magnetic resonance imaging of intact animals, provides support for the biomechanical analysis. These results suggest how a soft grasper can work during feeding, and suggest novel designs for artificial soft graspers.

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Section: Discussionmentioning

confidence: 99%

Soft-surface grasping: radular opening in Aplysia californica

Kehl

et al. 2019

Journal of Experimental Biology

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“…Compared to the previous work, a larger part of the fingertip is cast in silicone rubber to enable a configuration with a larger number of sensors. This also contributes to an improved grasping behaviour as the silicone rubber is more elastic and has a higher friction coefficient compared to the 3D printed material [50].…”

Section: Manufacturing Processmentioning

confidence: 99%

An Embedded, Multi-Modal Sensor System for Scalable Robotic and Prosthetic Hand Fingers

Weiner

Neef

Shibata

et al. 2019

Sensors

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Grasping and manipulation with anthropomorphic robotic and prosthetic hands presents a scientific challenge regarding mechanical design, sensor system, and control. Apart from the mechanical design of such hands, embedding sensors needed for closed-loop control of grasping tasks remains a hard problem due to limited space and required high level of integration of different components. In this paper we present a scalable design model of artificial fingers, which combines mechanical design and embedded electronics with a sophisticated multi-modal sensor system consisting of sensors for sensing normal and shear force, distance, acceleration, temperature, and joint angles. The design is fully parametric, allowing automated scaling of the fingers to arbitrary dimensions in the human hand spectrum. To this end, the electronic parts are composed of interchangeable modules that facilitate the mechanical scaling of the fingers and are fully enclosed by the mechanical parts of the finger. The resulting design model allows deriving freely scalable and multimodally sensorised fingers for robotic and prosthetic hands. Four physical demonstrators are assembled and tested to evaluate the approach.

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“…For example, fingertips are especially relevant during manipulating a small object [2]. A clear shortcoming of our previous work was that it was applied only to flat surfaces, but multicurved fingertips are beneficial [8]. In general, many soft skin sensors can be implemented for a flat or cylindrical surface, but only a few of them can be utilized to cover a multicurved surface [2] [9] [10].…”

Section: Introductionmentioning

confidence: 99%

Covering a Robot Fingertip With uSkin: A Soft Electronic Skin With Distributed 3-Axis Force Sensitive Elements for Robot Hands

Tomo

Schmitz

Wong

et al. 2018

IEEE Robot. Autom. Lett.

Self Cite

120

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Distributed tactile sensing is crucial to perform stable, subtle, and precise manipulation so that a robot can recognize and handle objects properly. However, currently existing skin sensors still have common problems such as complex and expensive production or are difficult to integrate into robot hands. In particular, a practical distributed soft skin sensor system that can cover various parts of the robot hand, measure force in 3axis, with a subcentimeter spatial density, and digital output at the same time does not exist yet. This paper discusses uSkin, a soft, distributed, 3-axis force sensor for robot hands and presents its implementation for multi-curved fingertips. The sensor is lowcost, easy to manufacture, and can measure normal and shear forces. The experimental results revealed that this sensor has 10% hysteresis for perpendicular force with a maximum range of 6 N. The Signal to Noise Ratio (SNR) value of 54 dB for 0.4 N load was achieved, which constitutes the state of the art for this kind of sensors. Evaluation experiments also showed that the distributed 3-axis load cells could produce vectors that represent the shape of objects. This opens the possibility that the sensor can be used for classifying different shapes. Furthermore, the fingertip sensor was installed on the Allegro hand and the changing force measurements when the robot is grasping an object are presented.

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A study on fingertip designs and their influences on performing stable prehension for robot hands

Cited by 5 publications

References 14 publications

Soft-surface grasping: radular opening in Aplysia californica

Soft-surface grasping: radular opening in Aplysia californica

An Embedded, Multi-Modal Sensor System for Scalable Robotic and Prosthetic Hand Fingers

Covering a Robot Fingertip With uSkin: A Soft Electronic Skin With Distributed 3-Axis Force Sensitive Elements for Robot Hands

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