A Periodic Deformation Mechanism of a Soft Actuator for Crawling and Grasping

2019 ◽  
Vol 4 (12) ◽  
pp. 1900653 ◽  
Author(s):  
Zhengjie Li ◽  
Rong Huang ◽  
Zishun Liu
Keyword(s):  
Deformation Mechanism ◽  
Soft Actuator ◽  
Periodic Deformation

Performance study of RTV-2 Silicone Rubber Material For Soft Actuator by Experimental and Numerical methods: The Effect of Inflation Pressure and Wall Thickness

2020 ◽  
Vol 17 (1) ◽  
pp. 7524-7532 ◽  
Author(s):  
Deepak D. ◽  
Nitesh Kumar ◽  
Shreyas P. Shetty ◽  
Saurabh Jain ◽  
Manoj Bhat
Keyword(s):  
Numerical Methods ◽  
Wall Thickness ◽  
Silicone Rubber ◽  
Inflation Pressure ◽  
Performance Study ◽  
Rubber Material ◽  
Soft Actuator ◽  
Alternative Materials ◽  
Load Carrying ◽  
Influential Parameters

The expensive nature of currently used materials in the soft robotic industry demands the consideration of alternative materials for fabrication. This work investigates the performance of RTV-2 grade silicone rubber for fabrication of a soft actuator. Initially, a cylindrical actuator is fabricated using this material and its performance is experimentally assessed for different pressures. Further, parametric variations of the effect of wall thickness and inflation pressure are studied by numerical methods. Results show that, both wall thickness and inflation pressure are influential parameters which affect the elongation behaviour of the actuator. Thin (1.5 mm) sectioned actuators produced 76.97% more elongation compared to thick sectioned, but the stress induced is 89.61 % higher. Whereas, the thick sectioned actuator (6 mm) showed a higher load transmitting capability. With change in wall thickness from 1.5 mm to 6 mm, the elongation is reduced by 76.97 %, 38.35 %, 21.05 % and 11.43 % at pressure 100 kPa, 75 kPa, 50 kPa and 25 kPa respectively. The induced stress is also found reduced by 89.61 %, 86.66 %, 84.46 % and 68.68 % at these pressures. The average load carrying capacity of the actuator is found to be directly proportional to its wall thickness and inflation pressure.

Actuation and dynamic mechanical characteristics of a core free flat dielectric electro-active polymer soft actuator

2020 ◽  
Vol 14 (4) ◽  
pp. 7396-7404
Author(s):  
Abdul Malek Abdul Wahab ◽  
Emiliano Rustighi ◽  
Zainudin A.
Keyword(s):  
Theoretical Model ◽  
Resonance Frequency ◽  
Dynamic Testing ◽  
Experimental Results ◽  
Percentage Error ◽  
Initial Tension ◽  
Average Percentage ◽  
Soft Actuator ◽  
Average Percentage Error ◽  
Mechanical Dynamics

Various complex shapes of dielectric electro-active polymer (DEAP) actuator have been promoted for several types of applications. In this study, the actuation and mechanical dynamics characteristics of a new core free flat DEAP soft actuator were investigated. This actuator was developed by Danfoss PolyPower. DC voltage of up to 2000 V was supplied for identifying the actuation characteristics of the actuator and compare with the existing formula. The operational frequency of the actuator was determined by dynamic testing. Then, the soft actuator has been modelled as a uniform bar rigidly fixed at one end and attached to mass at another end. Results from the theoretical model were compared with the experimental results. It was found that the deformation of the current actuator was quadratic proportional to the voltage supplied. It was found that experimental results and theory were not in good agreement for low and high voltage with average percentage error are 104% and 20.7%, respectively. The resonance frequency of the actuator was near 14 Hz. Mass of load added, inhomogeneity and initial tension significantly affected the resonance frequency of the soft actuator. The experimental results were consistent with the theoretical model at zero load. However, due to inhomogeneity, the frequency response function’s plot underlines a poor prediction where the theoretical calculation was far from experimental results as values of load increasing with the average percentage error 15.7%. Hence, it shows the proposed analytical procedure not suitable to provide accurate natural frequency for the DEAP soft actuator.

QUASI--SUPERPLASTICITY AND DEFORMATION MECHANISM OF ULTRALIGHT β SOLID SOLUTION Mg--11Li--3Zn ALLOY

2013 ◽  
Vol 48 (2) ◽  
pp. 250-256 ◽  
Author(s):  
Furong CAO ◽  
Hua DING ◽  
Zhaodong WANG ◽  
Yinglong LI ◽  
Renguo GUAN ◽  
...  
Keyword(s):  
Solid Solution ◽  
Deformation Mechanism

scholarly journals High-cycle-life and high-loading copolymer network with potential application as a soft actuator

2019 ◽  
Vol 182 ◽  
pp. 108010 ◽  
Author(s):  
Hafeez Ur Rehman ◽  
Yujie Chen ◽  
Mikael S. Hedenqvist ◽  
Radan Pathan ◽  
Hezhou Liu ◽  
...  
Keyword(s):  
Potential Application ◽  
Cycle Life ◽  
High Loading ◽  
Soft Actuator ◽  
Copolymer Network

Ferrite formation and its effect on deformation mechanism of wire arc additive manufactured 308 L stainless steel

2021 ◽  
Vol 550 ◽  
pp. 152933
Author(s):  
Yajing Li ◽  
Ying Luo ◽  
Jianghua Li ◽  
Danrong Song ◽  
Bin Xu ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Deformation Mechanism ◽  
Ferrite Formation

scholarly journals Sensuator: A Hybrid Sensor–Actuator Approach to Soft Robotic Proprioception Using Recurrent Neural Networks

Actuators ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 30
Author(s):  
Pornthep Preechayasomboon ◽  
Eric Rombokas
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Linear Models ◽  
Open Loop ◽  
Proof Of Concept ◽  
State Estimator ◽  
Loop Control ◽  
Practical Applications ◽  
Soft Actuator ◽  
The Cost

Soft robotic actuators are now being used in practical applications; however, they are often limited to open-loop control that relies on the inherent compliance of the actuator. Achieving human-like manipulation and grasping with soft robotic actuators requires at least some form of sensing, which often comes at the cost of complex fabrication and purposefully built sensor structures. In this paper, we utilize the actuating fluid itself as a sensing medium to achieve high-fidelity proprioception in a soft actuator. As our sensors are somewhat unstructured, their readings are difficult to interpret using linear models. We therefore present a proof of concept of a method for deriving the pose of the soft actuator using recurrent neural networks. We present the experimental setup and our learned state estimator to show that our method is viable for achieving proprioception and is also robust to common sensor failures.

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