자율무인잠수정의 주행경로 인식을 위한 퍼지칼만필터 설계에 관한 연구

Abstract

Recently, the global issues about the depletion of fossil fuels have brought much concerns about the technology for the collection of marin resources. The marin plant is playing an important role in obtaining resources from ocean. Since the human activity is restricted in marine environment, the autonomous underwater vehicles (AUV) have been developed to conduct tasks in the marin environment. AUV are categorized into wireless AUV and wired AUV. Currently, the AUV using tethering cables communicating between AUV and users have been widely used. However, they have limited in their working ranges due to the tethering cables. For this reason, the needs of advanced wireless AUV are increasing. The autonomous navigation system is required for the AUV to carry out the tasks in remote areas. The navigation systems are categorized into dead reckoning navigations, which utilizing environmental data from mounted sensors, and positioning navigations. Although the dead reckoning navigation can correspond well to the environmental variations based on the data from sensors, the error accumulation occurs while the navigation algorithms, which consisting of derivative equations, are running. In contrast, positioning navigation is less affected from the error accumulation problems due to the use of real time data from GPS and acoustic sensors. However, the vehicle needs to rise to the surface periodically to receive data from GPS, and the acoustic sensor system is easily affected by the condition of sea water, such as temperature, salinity, and density. For this reason, the signal processing technique to reduce the error accumulation has been developing along with improving the precision of sensors in dead reckoning navigation systems. The paper investigated the path recognition of AUV using signal processing technique with fuzzy logic and kalman filtering. To develop the kalman filter, a model that simulates output signals from sensors was developed. Also this study investigated an algorithm that detecting moving paths when the movement of vehicle occurs to reduce the error accumulation while tracking paths. When the moving of the AUV is detected, the fuzzy logic and kalman filter are activated to process signals. In order to verify the navigation system, a simulator, enabling the straight line motion and circular motion, was built. Finally, the best signal processing method between the fuzzy logic and kalman filter was selected and applied to the performance verification of the AUV.