Mechatronic design of an integrated robotic hand

Purpose – The subject of the paper is the mechatronic design of a novel robotic hand, cassino-underactuated-multifinger-hand (Ca.U.M.Ha.), along with its prototype and the experimental analysis of its grasping of soft and rigid objects with different shapes, sizes and materials. The paper aims to discuss these issues. Design/methodology/approach – Ca.U.M.Ha. is designed with four identical underactuated fingers and an opposing thumb, all joined to a rigid palm and actuated by means of double-acting pneumatic cylinders. In particular, each underactuated finger with three phalanxes and one actuator is able to grasp cylindrical objects with different shapes and sizes, while the common electropneumatic operation of the four underactuated fingers gives an additional auto-adaptability to grasp objects with irregular shapes. Moreover, the actuating force control is allowed by a closed-loop pressure control within the pushing chambers of the pneumatic cylinders of the four underactuated fingers, because of a pair of two-way/two-position pulse-width-modulation (PWM) modulated pneumatic digital valves, which can also be operated under ON/OFF modes. Findings – The grasping of soft and rigid objects with different shapes, sizes and materials is a very difficult task that requires a complex mechatronic design, as proposed and developed worldwide, while Ca.U.M.Ha. offers these performances through only a single ON/OFF or analogue signal. Practical implications – Ca.U.M.Ha. could find several practical applications in industrial environments since it is characterized by a robust and low-cost mechatronic design, flexibility and easy control, which are based on the use of easy-running components. Originality/value – Ca.U.M.Ha. shows a novel mechatronic design that is based on a robust mechanical design and an easy operation and control with high dexterity and reliability to perform a safe grasp of objects with different shapes, sizes and materials.

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A Modified Optimal Control Strategy for a Five-Finger Robotic Hand

International Journal of Robotics and Automation Technology ◽

10.15377/2409-9694.2014.01.01.1 ◽

2014 ◽

Vol 1 (1) ◽

pp. 3-10 ◽

Cited By ~ 4

Author(s):

Cheng-Hung Chen ◽

◽

D. Naidu

Keyword(s):

Optimal Control ◽

Control Strategy ◽

Robotic Hand ◽

Optimal Control Strategy

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Mechatronic Design with Automatic Constraint Handling Using Evolutionary Algorithms

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)39229-7 ◽

2000 ◽

Vol 33 (26) ◽

pp. 711-716

Author(s):

Mattias Wahde ◽

Hans Sandholt

Keyword(s):

Evolutionary Algorithms ◽

Constraint Handling ◽

Mechatronic Design

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A simplified model of a multi-jointed mechanical finger calibrated with experimental data by vision system

Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics ◽

10.1177/1464419320955115 ◽

2021 ◽

Vol 235 (1) ◽

pp. 164-175

Author(s):

C Cosenza ◽

V Niola ◽

S Savino

Keyword(s):

Experimental Data ◽

Vision System ◽

Control Strategies ◽

Image Correlation ◽

Robotic Hand ◽

Prosthetic Device ◽

Prosthetic Hands ◽

Mechanical Hand ◽

Free Mode ◽

Mechanical Finger

The development of suitable models for mechanical fingers, whether they are part of prosthetic device or of a robotic hand, is a powerful tool to predict the behaviour of their components since the early stages of design, especially for underactuated mechanisms. Experimental data can improve the reliability of such models and promote their application to build proper control strategies especially for prosthetic hands. Here, we have developed a multi-jointed model of a mechanical finger. The finger is part of the Federica hand: an underactuated mechanical hand that was conceived for prosthetic purpose. The model accounts for friction phenomena in the finger and it is tuned with experimental data acquired through a digital image correlation device. The model allowed us to write kinematics relations of the phalanges and evaluate finger configurations in relation to the closure velocity. Moreover, it was possible to estimate the tendon force and the work analysis occurring during the closure tasks, both in free mode and in presence of objects.

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