Yeonsik Kang

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In this paper, we present various formation keeping ability of multiple unmanned ground vehicles (UGV) using nonlinear model predictive control based method. The high-level formation control problems of multiple UGVs such as smooth path planning and collision avoidance between UGVs are solved using distributed nonlinear model predictive control method which(More)
This paper presents a practical approach for a nonlinear model predictive control scheme with collision avoidance which is implemented on a mobile robot with two differential wheels. In model predictive control, also called receding horizon control, cost function is formulated to minimize tracking error. The optimal control input is solving a discrete(More)
Today, there are increased interest and various efforts in using cognitive architectures to control robotic platforms. Recent advances to essential capabilities in robots contributed to this trend, which tries to meet the increased demand for high-level control mechanisms. The tradition of cognitive architectures aims for general intelligence, and they have(More)
We propose an algorithm of reliable detection of line for unmanned navigation of mobile robots using sensor fusion. To detect the distance and the angle between the robot and the line, we use a vision sensor system and a laser range finder (LRF). Each sensor system runs its own extended Kalman filter (EKF) to estimate the distance and orientation of the(More)
This paper proposes a path planner for a humanoid robot to enhance its performance in terms of the human-robot interaction perspective. From the human point of view, the proposed method uses the time index that can generate a path that humans feel to be natural. In terms of the robot, the proposed method yields a waypoint-based path, the simplicity of which(More)
This paper presents an adaptive Nonlinear Model Predictive Control (NMPC) for the path tracking control of a fixed-wing unmanned aircraft. The objective is to minimize the mean and maximum error between the reference trajectory and the UAV. Navigating in a cluttered environment requires accurate tracking. However linear controllers cannot provide good(More)