scholarly journals Design and Preliminary Evaluation of A Biomimetic Underwater Robot with Undulating Fin Propulsion

Author(s):  
Lei Liu ◽  
Yaxin Li ◽  
Yu Wang ◽  
Xinyu Ma
2015 ◽  
Vol 743 ◽  
pp. 150-156
Author(s):  
Hai Jun Xu ◽  
Lei Zhang ◽  
Cun Yun Pan ◽  
Xiang Zhang

Fish Swimming in MPF (Media and/or Paired Fin) mode has unique hydrodynamic characters and special application in resource exploration underwater. Inspired of the flexible shape and motion of undulating fin of “Nilotic Ghost” fish, a Hydraulic-driven Bionic Undulating Robot (HBUR) is developed and studied in the paper based on CFD method, to investigate the flexible characteristics of shape adaptation and hydrodynamics of HBUR fin, which has great significance for the propelling safety of HBUR underwater. In this paper, a mathematical model is brought forward to indicate the undulating motion of HBUR, which is formed by sequentially and periodically swing motions of Hydraulic Swing Actors (HSAs), and then the CFD method is introduced to calculate the hydro-forces when undulating shape of HBUR fin are distorted, because of distraction underwater. Results show that HBUR could produce propelling forces even when some of the HSAs are restricted from swinging, and shape adaptation ability of different part on HBUR fin is different, where the middle part is worse than the two sides. The propelling forces generated by undulating motion the rest of HBUR fin could be used to get the underwater robot out of trouble itself, and then undulating shape will restore to normal state.


1989 ◽  
Vol 32 (3) ◽  
pp. 681-687 ◽  
Author(s):  
C. Formby ◽  
B. Albritton ◽  
I. M. Rivera

We describe preliminary attempts to fit a mathematical function to the slow-component eye velocity (SCV) over the time course of caloric-induced nystagmus. Initially, we consider a Weibull equation with three parameters. These parameters are estimated by a least-squares procedure to fit digitized SCV data. We present examples of SCV data and fitted curves to show how adjustments in the parameters of the model affect the fitted curve. The best fitting parameters are presented for curves fit to 120 warm caloric responses. The fitting parameters and the efficacy of the fitted curves are compared before and after the SCV data were smoothed to reduce response variability. We also consider a more flexible four-parameter Weibull equation that, for 98% of the smoothed caloric responses, yields fits that describe the data more precisely than a line through the mean. Finally, we consider advantages and problems in fitting the Weibull function to caloric data.


2013 ◽  
Author(s):  
Joseph D. Lohman ◽  
Albert Wahl ◽  
Robert M. Carter

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