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Technical Brief

Fuzzy Control of a Robotic Finger Actuated by Shape Memory Alloy Wires

[+] Author and Article Information
André F. C. Silva

Mechanical Engineering Department,
Federal University of Paraiba Cidade Universitária,
João Pessoa 58051-900, PB, Brazil
e-mail: andrefellipecs@gmail.com

Simplício A. da Silva

Mechanical Engineering Department,
Federal University of Paraiba Cidade Universitária,
João Pessoa 58051-900, PB, Brazil
e-mail: simplicioarnaud@gmail.com

Alexsandro J. V. dos Santos

Electrical Engineering Department,
Federal University of Paraiba Cidade Universitária,
João Pessoa 58051-900, PB, Brazil
e-mail: alexsandro@cear.ufpb.br

Andreas Ries

Electrical Engineering Department,
Federal University of Paraiba Cidade Universitária,
João Pessoa 58051-900, PB, Brazil
e-mail: ries750@yahoo.com.br

Cícero R. Souto

Electrical Engineering Department,
Federal University of Paraiba Cidade Universitária,
João Pessoa 58051-900, PB, Brazil
e-mail: cicerosouto@cear.ufpb.br

Carlos J. de Araújo

Mechanical Engineering Department,
Federal University of Campina Grande,
Av. Aprígio Veloso 882,
Campina Grande 58429-140, PB, Brazil
e-mail: carlos.araujo@ufcg.edu.br

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 16, 2017; final manuscript received November 21, 2017; published online December 22, 2017. Assoc. Editor: Evangelos Papadopoulos.

J. Dyn. Sys., Meas., Control 140(6), 064502 (Dec 22, 2017) (7 pages) Paper No: DS-17-1255; doi: 10.1115/1.4038652 History: Received May 16, 2017; Revised November 21, 2017

This paper presents the development of a robotic finger driven by nonconventional actuators, consisting of thin shape memory alloy (SMA) wires. In order to monitor and control the angles formed by each phalanx, a specific system for capturing and interpreting digital images was implemented. By image processing, this system is capable to determine the angles without the need for installation of phalanx rotation sensors, leading to weight and volume reduction of the prototype. For this artificial vision system, a simple camera with a fuzzy logic control technique was used, which was very effective in monitoring the position of the robotic finger.

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References

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Figures

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Fig. 4

Schematic representation of data acquisition by the camera

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Fig. 5

Control of the PP in closed-loop. Top: desired angle versus measured angle. Bottom: percentage error of the fuzzy control.

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Fig. 3

Computer vision system for position control of the SMA robotic finger. Reference coordinates (a) and camera-finger configuration for data acquisition (b).

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Fig. 2

The fuzzy membership functions adopted for each variable set

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Fig. 6

Control of the MP in closed-loop. Top: desired angle versus measured angle. Bottom: percentage error of the fuzzy control.

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Fig. 7

Control of the DP in closed-loop. Top: desired angle versus measured angle. Bottom: percentage error of the fuzzy control.

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Fig. 1

Dorsal view of the human hand: (a) proximal, (b) middle, and (c) distal phalanx; (1) MCP, (2) PIP, and (3) DIP joint

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Fig. 8

Activation of the MP for a sequence of two positions. Top: reference angle. Middle: defuzzification output. Bottom: actual current in the SMA actuator.

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