A5022956507- Robotic Path Planning Algorithms
- Target Tracking and Data Fusion in Sensor Networks
- Inertial Sensor and Navigation
- Robotics and Sensor-Based Localization
- Machine Fault Diagnosis Techniques
- UAV Applications and Optimization
- Guidance and Control Systems
- Aerospace Engineering and Control Systems
- Fault Detection and Control Systems
- Aerospace and Aviation Technology
- Anomaly Detection Techniques and Applications
Pusan National University
2021-2024
This paper presents a vision-based adaptive tracking and landing method for multirotor Unmanned Aerial Vehicles (UAVs), designed safe recovery amid propulsion system failures that reduce maneuverability responsiveness. The addresses challenges posed by external disturbances such as wind agile target movements, specifically, considering control limitations caused failures. Building on our previous research in actuator fault detection tolerance, approach employs modified pure pursuit guidance...
This article presents a novel approach for detecting and isolating faulty actuators in highly redundant Multirotor UAVs using cascaded Deep Neural Network (DNN) models. The proposed Fault Detection Isolation (FDI) framework combines Long Short-Term Memory (LSTM)-based fault detection actuator locator models to achieve real-time monitoring. study focuses on Hexadecarotor multirotor UAV equipped with sixteen rotors. To tackle the complexity of FDI resulting from redundancy, partitioning...
The use of unmanned aerial vehicle (UAV) applications has grown rapidly over the past decade with introduction low-cost microelectromechanical system (MEMS)-based sensors that measure angular velocity, gravity, and magnetic field, which are important for an object orientation determination. However, also been limited because their readings easily distorted by unwanted internal and/or external noise signals such as environmental disturbance, lead to errors in attitude heading estimation...
In various applications, the extended Kalman filter (EKF) has been vital in estimating a vehicle’s translational and angular motion 3-dimensional (3D) space. It is also essential for fusion of data from multiple sensors. However, EKF to perform effectively, optimal process noise covariance matrix (Q) measurement (R) must be chosen correctly. The use challenging due need an easy mechanism select Q R values. As result, this research focused on developing algorithm that can easily applied...
Presently, multirotor unmanned aerial vehicles (UAV) are utilized in numerous applications. Their design governs the system’s controllability and operation performance by influencing achievable forces moments produced. However, unexpected causalities, such as actuator failure, adversely affect their controllability, which raises safety concerns about service. On other hand, flexibility allows further optimization for various requirements, including failure tolerance. Thus, this study...