Hyo-Sang Shin

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This paper proposes a behaviour recognition methodology for ground vehicles moving within road traffic using unmanned aerial vehicles in order to identify suspicious or abnormal behaviour. With the target information acquired by unmanned aerial vehicles and estimated by filtering techniques, ground vehicle behaviour is first classified into representative(More)
This paper introduces a new strategy to improve the performance and reliability of multi-rotor vehicles. The strategy uses a dual axes tilting propeller in order to generate control actions. The mechanisms of actuation are: gyroscopic torques, thrust vectoring and differential thrusting. A realisation of the new concept is detailed in this paper. The model(More)
This paper presents a coordinated standoff tracking methodology of groups of moving targets using multiple UAVs. The vector field guidance approach is first applied to track a group of targets for a single UAV 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(More)
This paper proposes UAV rendezvous and standoff tracking guidance laws against a moving target using differential geometry. Searching and subsequent tracking of moving ground based target is one of the primary capabilities of cooperative UAVs. In performing such missions, UAVs are to approach a target and keep a certain distance, known as a standoff(More)
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(More)
This paper proposes an airborne behaviour monitoring methodology of ground vehicles based on a statistical learning approach with domain knowledge given by road map information. To monitor and track the moving ground target using UAVs aboard a moving target indicator, an interactive multiple model (IMM) filter is firstly applied. The IMM filter consists of(More)
This study proposes an optimal resource allocation algorithm of multiple UAVs with cooperative path planning using a geometric approach. The focus of the resource allocation is on mission and task completion, also known as feasibility whilst coping with operational and physical constraints of UAVs. Therefore, this study first introduces a geometric path(More)
In this paper we present a decentralised algorithm to solve the Task Allocation problem. Given a set of tasks and a set of robots each with its own utility function, this problem concerns the non-overlapping allocation of tasks to agents maximising the sum of the robot's utility functions. Our algorithm provides a constant factor approximation of (1 - 1/e(More)
This paper proposes a novel game-theoretical autonomous decision-making framework to address a task allocation problem for a swarm of multiple agents. We consider cooperation of self-interested agents and show that agents who have social inhibition can converge to a Nash stable partition (i.e., social agreement) using our proposed decentralised algorithm(More)