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http://dx.doi.org/10.3795/KSME-A.2016.40.7.629

Statistical Estimation of Motion Trajectories of Falling Petals Based on Particle Filtering  

Lee, Jae Woo (Dept. of Creative Science and Technology, Waseda Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.40, no.7, 2016 , pp. 629-635 More about this Journal
Abstract
This paper presents a method for predicting and tracking the irregular motion of bio-systems, - such as petals of flowers, butterflies or seeds of dandelion - based on the particle filtering theory. In bio-inspired system design, the ability to predict the dynamic motion of particles through adequate, experimentally verified models is important. The modeling of petal particle systems falling in air was carried out using the Bayesian probability rule. The experimental results show that the suggested method has good predictive power in the case of random disturbances induced by the turbulence of air.
Keywords
Particle Filter; Bayes Filter; Bio System; Motion Estimation; Petal Flying;
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