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Sungjoon Choi,Seung-Young Park,Sang-Im Yoo 한국자기학회 2021 한국자기학회 학술연구발표회 논문개요집 Vol.31 No.1
The microwave absorption properties of Zn-substituted SrW-type hexaferrites (SrZn<sub>x</sub>Fe<sub>2-x</sub>Fe<sub>16</sub>O27; SrZn<sub>x</sub>Fe<sub>2-x</sub>W, where x = 0.0, 0.25, 0.5, 1.0, and 2.0) in Ka-band (26.5−40 GHz) were studied. The Zn<sup>2+</sup> ion substitution for the Fe<sup>2+</sup> ion is well known to increase both real and imaginary parts of permeability (μr = μʹ − jμʹʹ) and permittivity (εr = εʹ − jεʹʹ) [1-2]. The SrZn<sub>x</sub>Fe<sub>2-x</sub>W (x=0.0, 0.25, 0.5, and 1.0) samples were annealed at the temperature region of 1000–1350 ˚C for 2 h in the PO<sub>2</sub> of 10<sup>-3</sup> atm while the SrZn<sub>2</sub>W was annealed in air to obtain single-phase. In order to measure microwave absorption properties, hexaferrite-epoxy resin composites were fabricated with the filler volume fractions (Vf) of 30, 50, 70, and 90%. The real and imaginary parts of permittivity and permeability of SrZn<sub>x</sub>Fe<sub>2-x</sub>W were measured by using a vector network analyzer (VNA, Agilent PNA N5525A) with a waveguide, and the reflection losses were calculated based on the transmission line theory [3]. The minimum reflection loss (RL<sub>min</sub>) of −68.4 dB at 28 GHz with the bandwidths of 2.48 GHz (26.50-28.98 GHz) below −20 dB, was achievable from a 0.64 mm-thick SrFe<sub>1.75</sub>Zn<sub>0.25</sub>W (x = 0.25) composite, indicating that partially Zn-substituted SrW-type hexaferrites are strong candidates as microwave absorber appropriate for 5G applications. Detailed results will be presented for discussion.
Real-time nonparametric reactive navigation of mobile robots in dynamic environments
Choi, Sungjoon,Kim, Eunwoo,Lee, Kyungjae,Oh, Songhwai Elsevier 2017 Robotics and autonomous systems Vol.91 No.-
<P><B>Abstract</B></P> <P>In this paper, we propose a nonparametric motion controller using Gaussian process regression for autonomous navigation in a dynamic environment. Particularly, we focus on its applicability to low-cost mobile robot platforms with low-performance processors. The proposed motion controller predicts future trajectories of pedestrians using the partially-observable egocentric view of a robot and controls a robot using both observed and predicted trajectories. Furthermore, a hierarchical motion controller is proposed by dividing the controller into multiple sub-controllers using a mixture-of-experts framework to further alleviate the computational cost. We also derive an efficient method to approximate the upper bound of the learning curve of Gaussian process regression, which can be used to determine the required number of training samples for the desired performance. The performance of the proposed method is extensively evaluated in simulations and validated experimentally using a Pioneer 3DX mobile robot with two Microsoft Kinect sensors. In particular, the proposed baseline and hierarchical motion controllers show over 65 % and 51 % improvements over a reactive planner and predictive vector field histogram, respectively, in terms of the collision rate.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A motion controller using for autonomous navigation in a dynamic environment is proposed. </LI> <LI> Limited sensing capabilities of a robot are effectively handled using the proposed motion model. </LI> <LI> An efficient method to approximate the learning curve of Gaussian process regression is proposed. </LI> </UL> </P>