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Technical Brief

Actuation Configurations of Bionic Hands for a Better Anthropomorphism Index

[+] Author and Article Information
Mahmoud Tavakoli

Institute for Systems and Robotics,
Department of Electrical and Computer Engineering,
University of Coimbra,
Coimbra, Portugal
e-mail: mahmoud@isr.uc.pt

Baptiste Enes, Lino Marques

Institute for Systems and Robotics,
Department of Electrical and Computer Engineering,
University of Coimbra,
Coimbra, Portugal

Thomas Feix

Department of Mechanical Engineering and Material Science,
Yale University,
New Haven, CT 06510
e-mail: thomasfeix@xief.net

Manuscript received April 6, 2015; final manuscript received December 10, 2015; published online March 7, 2016. Assoc. Editor: Jun Ueda.

J. Mechanisms Robotics 8(4), 044502 (Mar 07, 2016) (4 pages) Paper No: JMR-15-1083; doi: 10.1115/1.4032405 History: Received April 06, 2015; Revised December 10, 2015

In this study, we analyze different actuation configurations for bionic hands in order to improve their level of anthropomorphism. We used a previously developed benchmark, the anthropomorphism index (AI), for 15 different actuation configurations of hands from one to five actuators. By comparing the AI of these configurations, we obtained important conclusions regarding the actuation strategy of the anthropomorphic hands with a limited number of actuators. Results show that the actuation configuration is very important for increasing the level of anthropomorphism of the hands. It is shown that with an appropriate actuation configuration, a configuration with lower number of actuators can result in a higher AI than a configuration with higher number of actuators. We also showed the best actuation configurations for each category of 1–5 actuators. Results can be used as a guideline for development of hands with high anthropomorphism in terms of grasping postures.

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Figures

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Fig. 5

Left to right: projection of the fingertip movements of configuration 1.0, 2.0, and 2.M for the ISR-Softhand in the latent space with a relative coverage of 0.25%, 0.33%, and 1.14%, respectively

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Fig. 6

Projection of the fingertip movements of configurations with three actuators with the ISR-Softhand. Left to right-configuration 3.0(0.33% coverage), 3.0 M(1.47% coverage), 3.1(1.63% coverage), 3.2(1.06% coverage), and 3.3(1.63% coverage).

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Fig. 7

Projection of the fingertip movements of configurations with four actuators with the ISR-Softhand. Left to right: 4.0(1.96% coverage), 4.0 M(1.55%), 4.1(1.88%), 4.2(0.33%), and 4.3(0.33%).

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Fig. 4

ISR-Softhand model

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Fig. 3

Number and symbol designations and the coordinate system to which the measurements are referenced

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Fig. 2

The evolution of the configurations from one to five actuators (without the ones with manual ab/ad of the thumb), and their corresponding AI for both hand kinematics. Arrows show the progression of the added actuator. Above the arrow: the added actuator, below arrow: the increases in the AI for each of the hands.

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Fig. 1

Tested hands, and projection of the fingertip movements to the latent space and their AI. Left: Sensorhand (AI = 0.25) [4], middle: Michelangelo (AI = 2.8) [5], and right: FRH-4 (AI = 5.2) [3,6].

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