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Diprotonated [28]Hexaphyrins(1.1.1.1.1.1): Triangular Antiaromatic Macrocycles
Ishida, Shin‐,ichiro,Higashino, Tomohiro,Mori, Shigeki,Mori, Hirotaka,Aratani, Naoki,Tanaka, Takayuki,Lim, Jong Min,Kim, Dongho,Osuka, Atsuhiro WILEY‐VCH Verlag 2014 Angewandte Chemie Vol.126 No.13
<P><B>Abstract</B></P><P>Protonation of <I>meso</I>‐aryl [28]hexaphyrins(1.1.1.1.1.1) triggered conformational changes. Whereas protonation with trifluoroacetic acid led to the formation of monoprotonated Möbius aromatic species, protonation with methanesulfonic acid led to the formation of diprotonated triangular antiaromatic species. A peripherally hexaphenylated [28]hexaphyrin was rationally designed and prepared to undergo diprotonation to favorably afford a triangular‐shaped antiaromatic species.</P>
Real Time Simulation for Obstacle Avoidance Using A*-EC Hybrid Path Planning Method
Katsushi Mitsutake,Shin-Ichiro Higashino 한국항공우주학회 2008 한국항공우주학회 학술발표회 논문집 Vol.- No.-
We have proposed an A*-EC hybrid path planning method for UAVs which can generate a waypoint traveling path considering terrain and obstacles in 3D environment. Although the path generated by the method is suboptimal, calculation time is short enough to use in real time. We have developed a real time Hardware-In-The-Loop (HIL) flight simulator to confirm that the method can be used in real time. In this paper, we show the results of the real time HIL simulation for the evaluation of the A*-EC hybrid method using onboard path planning computer which is planned to be used in flight testing and recorded actual weather information as moving obstacles.
Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem
Omagari, Hiroki,Higashino, Shin-Ichiro The Korean Society for Aeronautical Space Sciences 2018 International Journal of Aeronautical and Space Sc Vol.19 No.1
In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.
Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem
Hiroki Omagari,Shin–Ichiro Higashino 한국항공우주학회 2018 International Journal of Aeronautical and Space Sc Vol.19 No.1
In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the “aspiration-point-based method” to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed “provisional-ideal-point-based method.” The proposed method defines a “penalty value” to search for feasible solutions. It also defines a new reference solution named “provisional-ideal point” to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.
Real-time Path Planning Method for Multiple UASs
Toshihiro Takebayashi,Makiko Ishii,Shin-Ichiro Higashino 한국항공우주학회 2008 한국항공우주학회 학술발표회 논문집 Vol.- No.-
The authors have proposed a method for the path planning of an Unmanned Aircraft System (UAS) and the simultaneous optimization of task assignment for multiple UASs using Evolutionary Computation (EC). This paper present a fast path planning method named Simplified Rule-Base EC hybrid (SRBEC) method and a fast task assignment method named Radial Segmentation Task Assignment (RSTA) method in order to use in real time. It also reports the results of the real-time simulations for the evaluation of RSTA and SRBEC methods.