This dissertation is supported by the Key Program of National Natural Science Foundation of China, titled “Autonomous ocean observation theory and technology for underwater vehicles”, and the Joint Funds of the National Natural Science Foundation of China, titled “Offshore Marine Environment Observation Technology Based on Underwater Mobile Platforms”. Combined with oceanographic observation requirements for high-precision data, this dissertation deeply studies the underwater vehicle planning and control methods for ocean observation, focusing on the following researches: the observation task optimization method for ocean feature field reconstruction; the underwater vehicle path planning method under the influence of ocean current; the multi-underwater vehicle control method for collaborative observation. This dissertation mainly includes the following contents. 1. Research on high-resolution ocean feature field reconstruction based on field observation data. Aiming at the problem that the current ocean model cannot make full use of the intensive observation data sampled by underwater vehicles to generate fine feature fields, a high-resolution ocean feature field reconstruction method based on the best linear unbiased estimation theory is proposed. This method is mainly driven by underwater vehicle observation data combining with the background field structure extracted from the ocean model prediction data. 2. To reduce the uncertainty of field reconstruction, this dissertation studies the optimization method of multi-underwater vehicle coverage observation. Aiming at the problem that the current sampling path will cause the local characteristic field reconstruction error to be significantly higher than other areas, a coverage observation optimization method based on regular observation mode is proposed to reduce the overall uncertainty of the characteristic field reconstruction in the region. Furthermore, without specifying the regular observation mode, an autonomous coverage observation optimization method driven by observation data is proposed, which further reduces the uncertainty of the field reconstruction. 3. Research on a path planning method of underwater vehicles in a time-varying strong flow field. Aiming at the problem that strong flow fields restrict the motion of underwater vehicles and affect the observation behavior, an improved minimum time path planning method based on level set is proposed to significantly improve the optimal path accuracy and ensure the feasibility of the obtained path in the strong flow field. 4. Research on a distributed path planning method of underwater vehicles based on underwater acoustic communication and flow field sharing. To solve the limited communication conditions in the marine environment affecting the information interaction between underwater vehicles, a single packet transmission strategy and a dynamic compression method based on the measured communication link quality are proposed to realize the distributed path planning of multiple underwater vehicles under the shared flow field. 5. Research on a cooperative formation control method for multiple underwater vehicles. Aiming at the problem that the multi-underwater vehicles cannot be controlled in real-time in the marine environment, which affects the performance of cooperative formation, an underwater vehicle state estimation model based on the self-perceived flow field is established. Based on the state estimation and a cooperative path tracking algorithm, a multi-underwater vehicle cooperative speed control and collaborative waypoint generation method is proposed to realize multi-underwater vehicle cooperative formation observation.