Autonomous underwater vehicles (AUVs) are unmanned vehicles that operate underwater. These vehicles can be used for various operations, including scanning the ocean floor in order to search for objects. In such operations, the AUV navigates close to the ocean floor, using its sonar systems to map this ocean floor. Before an AUV is launched on a search operation, usually very little is known about the underwater conditions at the search location. Currently, the AUV’s coverage path is often defined before the start of the operation. However, the coverage path depends on the quality of the sonar images, which in turn depend on the unknown and varying underwater conditions. Therefore, it is unlikely that the predefined coverage path is optimal. In this final thesis project a coverage path planner is developed, which autonomously adapts the AUV’s coverage path to the changing underwater conditions during an operation. Since the radio waves carrying the global positioning system (GPS) signal do not travel far in seawater, the AUV needs to keep track of its location using an inertial navigation system (INS). Unfortunately, the error on the location measurements obtained from an INS grows over time, causing the AUV’s believed trajectory to differ significantly from the AUV’s true trajectory. As a result, parts of the search area might be believed to have been covered, while these parts have in reality not been visited. Taking the AUV’s uncertain trajectory into account thus increases the complexity of the coverage path planning problem. In order to keep track of which parts of the search area have been covered, and to which extent, a coverage map of the search area is maintained during an operation. This coverage map is constructed such that it takes the uncertainty on the AUV’s location measurements into account. Three different coverage path planners have been developed that use this coverage map to autonomously plan the AUV’s coverage path during an operation. The three different coverage path planners have been implemented in MATLAB, and they have been evaluated in a simulation framework developed by TNO. The simulation results show that all three coverage path planners consistently achieve the required coverage of the search area, in a scenario where no large changes in the underwater conditions occurred. Furthermore, one of the coverage path planners has been evaluated in three scenarios where large changes during the operation did occur. Halfway during these scenarios, either the strength of the underwater currents increased, the required coverage of the search area increased, or one of the AUV’s sonar systems broke down. In all of these scenarios, the coverage path planner successfully adapted the coverage path such that the required coverage of the search area was still achieved.