This paper presents the design and experimental validation of an intelligent tire alignment and lifting control system for an under-vehicle autonomous parking robot. The proposed system enables the robot to autonomously enter beneath a vehicle, recognize tire positions using a LiDAR-based sensing module, and perform precise lifting through a fork-type mechanism. A YOLOv8 instance segmentation algorithm is employed to detect tire regions from LiDAR point cloud data and estimate their geometric centers. The detected tire positions are then matched with a vehicle database to determine the correct alignment for lifting. Experiments were conducted on three different vehicle types under various surface conditions. The results show that the proposed system achieved a tire recognition accuracy exceeding 95%, a lifting success rate of 100%, and an average lifting operation time of 12.3 seconds. These results demonstrate the reliability and practicality of the proposed method for real-world autonomous parking applications.

본 연구는 레벨 3 자율주행의 운전이양권(TOR) 안전성 향상을 위해, 기존 행동 기반 감지 방식의 한계를 극복하 는 운전자 모니터링 시스템(DMS)을 개발했다. 차량의 미러 내장형 RGBW 카메라를 이용한 비접촉 원격 광용적맥 파(rPPG) 기술로 운전자의 심박수를 실시간 측정하고, 심박변이도(HRV) 분석을 통해 졸음, 스트레스 등 운전자의 각성 수준을 판단한다. 딥러닝 기반 얼굴 인식, 신호 처리, 패턴 인식 알고리즘을 통합하여 시스템을 구현했다. 총 28명을 대상으로 105시간 이상의 실제 도로 환경에서 검증한 결과, 심전도(ECG) 대비 85.14%의 심박수 측정 정확 도와 90.81%의 상태 판단 정확도를 달성했다. 본 연구는 생체신호 기반의 운전자 상태 평가가 TOR 판단의 신뢰성 을 높이는 핵심 기술이 될 수 있음을 실증했다.

In this study, a ship motion control system design method is introduced for autonomous ships. Some related research results and technologies for autonomous ships have already been developed and applied to testing ships. Recently, the Norwegian Maritime Authority and the Coastal Administration have signed an agreement and started to test autonomous ships in the defined area. Considering recent technology trends and background, in this paper, the authors also try to develop autonomous ship control technologies. In the designed control system, an observer is introduced to estimate unmeasurable system states. Based on the servosystem with state estimator, ship motion control experiment is performed to evaluate control performance using a model ship in water basin.

In this study, a ship motion control system design method is introduced for autonomous ships. Some related research results and technologies for autonomous ships have already been developed and applied to ships. For example, the Norwegian Maritime Authority and the Coastal Administration have signed an agreement that allows to test of autonomous ships in the defined area (port to port). Many countries and industries are pursuing to realize the autonomous vessel in the real world. In this paper, the authors try to develop related technology. As basic research, a ship model of the pilot vessel is developed and physical parameters are identified by experiment and simulations. Using the mathematical ship model, a control system is designed and control performance is evaluated by simulations.

This paper presents a control and operation system for a remotely operated vehicle (ROV). The ROV used in the study was equipped with a manipulator and is being developed for underwater exploration and autonomous underwater working. Precision position and attitude control ability is essential for underwater operation using a manipulator. For propulsion, the ROV is equipped with eight thrusters, the number of those are more than six degrees-of-freedom. Four of them are in charge of surge, sway, and yaw motion, and the other four are responsible for heave, roll, and pitch motion. Therefore, it is more efficient to integrate the management of the thrusters rather than control them individually. In this paper, a thrust allocation method for thruster management is presented, and the design of a feedback controller using sensor data is described. The software for the ROV operation consists of a robot operating system that can efficiently process data between multiple hardware platforms. Through experimental analysis, the validity of the control system performance was verified.

In this paper, a localization algorithm and an autonomous controller for PETASUS system II which is an underwater vehicle-manipulator system, are proposed. To estimate its position and to identify manipulation targets in a structured environment, a multi-rate extended Kalman filter is developed, where map information and data from inertial sensors, sonar sensors, and vision sensors are used. In addition, a three layered control structure is proposed as a controller for autonomy. By this controller, PETASUS system II is able to generate waypoints and make decisions on its own behaviors. Experiment results are provided for verifying proposed algorithms.