In the work of the Control Engineering research group of the Department of Computer Science, Electrical and Space Engineering, Signals and systems at Luleå University of Technology a need had arisen for a path planning algorithm. The ongoing research with Unmanned Aerial Vehicles(UAVs) had so far been done with any complicated paths being created manually with waypoints set by the uses. To remove this labourious part of the experimental process a path should be generated automatically by simply providing a program with the position of the UAV, the goal to which the user wants it to move, as well as information about the UAV's surroundings in the form of a 3D map.In addition to simply finding an available path through a  3D environment the path should also be adapted to the risks that the physical environment poses to a flying robot. This was achieved by adapting a previously developed algorithm, which did the simple path planning task well, by adding a penalty weight to areas near obstacles, pushing the generated path away from them.The planner was developed working with the OctoMap map system which represents the physical world by segmenting it into cubes of either open or occupied space. The open segments of these maps could then be used as vertices of a graph that the planning algorithm could traverse.The algorithm itself was written in C++ as a node of the Robot Operating System(ROS) software framework to allow it to smoothly interact with previously developed software used by the Control Engineering Robotics Group.The program was tested by simulations where the path planner ROS node was sent maps as well as UAV position and intended goal. These simulations provided valid paths, with the performance of the algorithm as well as the quality of the paths being evaluated for varying configurations of the planners parameters.The planner works well in simulation and is deemed ready for use in practical experiments.