Rui Hirokawa

A Small UAV for Immediate Hazard Map Generation

An unmanned aerial vehicle (UAV) system providing quick response imagery for natural disaster assessment was developed. A prototype UAV and on-board software using a GPS navigation system were developed for this purpose. The flight performance was evaluated by 6DOF simulations and rigorous flight tests. In the proposed system, collected images by an on-board digital camera is transmitted in real-time to a spatial temporal GIS to share the information. The usability of the small UAV system was qualified by a flight experiment in a city-wide emergency evacuation drill.

Suboptimal Gain Functions of Feedback Particle Filter Derived from Continuation Method

This paper proposes a novel numerical approach to obtain gain functions of feedback particle filters (FPFs). Recent researches have provided several methods of control-based formulation for particle filters (PFs). These new PFs control transition between prior and posterior particles based on Bayes’ rule. FPF is one of them, and FPF uses feedback control based on optimal control theory to adjust probability density of the posteriors. The optimal gain function needs to be obtained at each time step by solving an Euler-Lagrange boundary value problem (E-L BVP) based on states of the particles. Therefore, several approximation approaches, such as Galerkin approximation and constant gain approximation, have been proposed as a suboptimal solution. Although these approaches provide a correct estimation for the nonlinear estimation problems, these have a difficulty of determining internal parameters called basis functions. Furthermore, clear guidelines for choosing basis functions are not provided yet. In this paper, we introduce a numerically suboptimal solution for the E-L BVPs without basis functions in order to enhance the ease of obtaining the gain functions. Our solution is a kind of continuation method, and the gain functions are obtained by updating the last gain functions at each time. Moreover, the E-L BVPs are approximated as forward differences in order to reduce the computational cost. We applied this method to popular benchmark problems of nonlinear estimation. It was found that our method exhibits lower estimation error than previous methods such as constant gain method.

Information collecting system based on aerial images obtained by a small UAV for disaster prevention

This paper presents a disaster prevention system using aerial images obtained by a small unmanned aerial vehicle (UAV). The immediate assessment of damage information and the continuous collection of information for constructing a revival plan are important for damage mitigation when natural disasters such as large earthquakes occur. In this study, we develop a small prototype UAV and onboard software using a GPS navigation system and propose a unique disaster prevention system that employs the small UAV and a geographical information system (GIS). We divide the period that follows a natural disaster on the basis of three processes, and we propose the use of the small UAV for gathering and integrating information into the GIS. We conducted field experiments to evaluate the proposed system employing the small UAV. From the results of our experiments, we concluded that the system is effective in disaster prevention.