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미모사 경촉 반응을 모사한 인공근육의 해석 · 실험 · 설계
김주희(Juhui Gim),명지영(Jiyoung Myung),전지나(Jina Jeon),성재경(Jaekyoung Sung),고민정(Minjung Go),김희경(Huikyeong Kim),임현지(Hyunji Lim),안창선(Changsun Ahn) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
This paper presents design of an artificial muscle inspired from leaf movements of Mimosa pudica, a sensitive plant. Mimosa pudica’s leaflets quickly contract by the osmosis pressure in the pulvinus when the leaflets are stimulated. The osmosis pressure of Mimosa pudica is based on Potassium ions and the contraction of leaflets happens in few seconds thanks to their high flux membranes. We analyze fast osmosis reactions of Mimosa pudica and design an exemplary artificial muscle based on the analysis results to mimic the fast osmosis responses. For the analysis of the fast osmosis responses, the osmosis phenomenon is mathematically modeled, analyzed and verified through several experiments. The analysis showed that the fast osmosis responses require large diffusion coefficient with high-flux membrane or small volume to surface ratio of osmosis system. Such high-flux membranes, as the Mimosa pudica’s membrane, are practically unavailable, we design micro-scaled system to achieve a small volume to surface ratio. The contraction and relaxation of the artificial muscle are realized by changes of local concentration of Potassium ions that can be aggregated by the controllable electric field. As a result, the designed artificial muscle shows speedy reactions as Mimosa pudica does.
김주희(Juhui Gim),안창선(Changsun Ahn),Huei Peng 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
Precise vehicle localization in urban canyons is difficult due to the GPS signal blocking caused by buildings. An observer can guess the current position by observing relative positions to the landmarks of which global positions are known. A vehicle can accurately observe its surroundings using a LiDAR. This paper proposes a landmark-based local positioning system using LiDAR as an alternative to GPS. First, the positioning system detects pole-like landmarks from the LiDAR point clouds using prior knowledge of pole-like objects. Then, the global positions of the detected landmarks are identified using information consisting of the geometric characteristics of the landmark itself and distances from other landmarks. Finally, vehicle position is reconstructed using the weighted average based on the number of LiDAR points observed landmarks. The proposed algorithm is validated in Mcity to show the potential of the landmark-based localization as an alternative to GPS/RTK, about a 3 cm-level accuracy.