김진환 교수

During the reentry to the atmosphere, certain ballistic missiles are known to undergo violent spiraling motions induced by aerodynamic resonance between roll and yaw/pitch modes. Successful interception of such spiraling targets is critically dependent on the performance of the target state estimator. Strong nonlinearities involved in the system dynamics and measurement equations together with sensor noise make this a challenging estimation task. The performance of an extended Kalman filter (EKF

Abstract Underwater visual inspection is an important task for checking the structural integrity and biofouling of the ship hull surface to improve the operational safety and efficiency of ships and floating vessels. This paper describes the development of an autonomous in‐water visual inspection system and its application to visual hull inspection of a full‐scale ship. The developed system includes a hardware vehicle platform and software algorithms for autonomous operation of the vehicle. The

The performance of ballistic target interception is critically dependent on the performance of the target state estimation. The estimation performance then strongly depends on the accuracy of the measurement model. The Gaussian uncertainty distribution has commonly been used for representing the statistical properties of sensor noise, due to its mathematical simplicity and effectiveness. However, seeker sensor measurements are often corrupted by glint noise which is highly non-Gaussian, and conv

This paper presents experimental validation results of autonomous collision avoidance algorithms using an unmanned surface vehicle (USV). For autonomous collision avoidance while following given waypoints, the existing line-of-sight (LOS) guidance and velocity obstacle (VO) algorithms are modifed and applied to this USV. The proposed collision avoidance algorithm considers the rule 13 to 17 in the international collision regulations (COLREGs) and provides a rule-compliant evasive path. The perfo

This paper addresses the development of an unmanned surface vehicle (USV) system by Team Angry-Nerds from KAIST for the inaugural Maritime RobotX Challenge competition, which was held on October 20-26, 2014, in Marina Bay, Singapore. The USV hardware was developed on a catamaran platform by integrating various system components, including propulsion, sensors, computer, power, and emergency systems. The competition comprised five mission tasks: 1) navigation and control, 2) underwater search and

Enhancing the performance of passive target tracking and trajectory estimation of marine traffic ships is focused using a monocular camera mounted on an unmanned surface vessel. To accurately estimate the trajectory of a target traffic ship, the relative bearing and range information between the observing ship and the target ship is required. Monocular vision provides bearing information with reasonable accuracy but with no explicit range information. The relative range information can be extrac

Global Positioning System (GPS) is an important component for marine vehicle navigation. However, GPS may not be reliable or even available in some situations, since GPS signals can be easily blocked or reflected by large structures and they are susceptible to jamming and spoofing attacks. In fact, radar is one of the standard navigation instruments, and radar measurements can be utilized for vehicle localization by coastline matching into a prior map. In this paper, a radar-based localization v

This paper proposes a new tracking controller for autonomous underwater vehicle-manipulator systems (UVMSs) using the concept of model reference adaptive control. It also addresses the detailed modeling and simulation of the dynamic coupling between an autonomous underwater vehicle and manipulator system based on Newton–Euler formulation scheme. The proposed adaptation control algorithm is used to estimate the unknown parameters online and compensate for the rest of the system dynamics. Specific

Collaborative operation with multiple unmanned systems has drawn significant research attention as the technology for the operation of a single unmanned system have gradually matured for practical applications. Multi-agent task allocation and assignment algorithms are crucial to the effective collaboration between multiple unmanned systems. This study addresses the optimal route planning problem with a group of multi-agent systems and proposes an efficient multi-agent task allocation algorithm.

During the reentry to the atmosphere, certain ballistic missiles are known to undergo violent spiraling motions induced by aerodynamic resonance between roll and yaw/pitch modes. Successful interception of such a spiraling target is critically dependent on the performance of the target state estimator. Strong nonlinearities involved in the system dynamics and measurement equations together with sensor noise make this a challenging estimation task. The performance of the Extended Kalman Filter, t