Hyondong Oh 교수

Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monito

This paper presents a methodology for coordinated standoff tracking of moving target groups using multiple unmanned aerial vehicles (UAVs). The vector field guidance approach for a single UAV is first applied to track a group of targets by defining a variable standoff orbit to be followed, which can keep all targets within the field-of-view of the UAV. A new feedforward term is included in the guidance command considering variable standoff distance, and the convergence of the vector field to the

This paper proposes a strategy for performing an efficient autonomous search to find an emitting source of sporadic cues of noisy information. We focus on the search for a source of unknown strength, releasing particles into the atmosphere where turbulence can cause irregular gradients and intermittent patches of sensory cues. Bayesian inference, implemented via the sequential Monte Carlo method, is used to update posterior probability distributions of the source location and strength in respons

This paper presents a road-network search route planning algorithm by which multiple autonomous vehicles are able to efficiently visit every road identified in the map in the context of the Chinese postman problem. Since the typical Chinese postman algorithm can be applied solely to a connected road-network in which ground vehicles are involved, it is modified to be used for a general type of road map including unconnected roads as well as the operational and physical constraints of unmanned aer

A coordinated standoff target tracking strategy using path shaping for multiple unmanned aerial vehicles (UAVs) is presented. In performing a tracking mission of a ground target of interest, UAVs are to approach a target and to keep a standoff distance from it with a prescribed inter-vehicle angular separation around the target in order to track it while acquiring accurate target information. Since fixed-wing UAVs without hovering capability fly efficiently at a nominal airspeed, it is desirable

This paper presents road-map-assisted standoff tracking of a ground vehicle using nonlinear model predictive control. In model predictive control, since the prediction of target movement plays an important role in tracking performance, this paper focuses on utilizing road-map information to enhance the estimation accuracy. For this, a practical road approximation algorithm is first proposed using constant curvature segments, and then nonlinear road-constrained Kalman filtering is followed. To ad