Wave Function Collapse (WFC) is a powerful generative algorithm, able to create locally-similar output based on a single example input. One of the inherent limitations of the original WFC is that it often requires users to understand its inner workings, and possibly make their own ad-hoc mods to achieve satisfactory results. Besides distracting from your creative task, this strongly reduces the algorithm's effective usefulness to a small group of technical users.

We propose a novel mixed-initiative approach to WFC, aimed at overcoming these drawbacks. These methods focus on providing intuitive control to its users, in a way that matches their usual creative workflow.

Among its main features, this approach provides (i) interactive navigation through design history, including controlled backtracking, (ii) precise manual editing of the output for direct expression of design intent, (iii) interactive manipulation of the tiles, and (iv) an initial layered approach towards post-processing algorithm output. These methods combined provide the required tools for users to tweak the global appearance of the output.

We evaluated a prototype implementation of our approach among game artists and other creative professionals, and concluded that its features were largely considered intuitive and supportive to express their creative intent.

Our challenge was to define a format for a mission plan, and develop an application which allows the users of the robot to create a mission plan effectively. This application should assist the user in the process of creating a mission plan as much as possible. Our client was Allseas who was already the sponsor of the LOBSTER project. During the research phase we learned that our application would be best suited for an offline environment, as the user would not necessarily have an internet connection due to being at sea. Furthermore, we learned that the application had to be easy to use and not too complex. Throughout the course of this project we worked with Scrum, our repository was hosted on GitHub, with Travis CI integrated to test our code. Using this we could see our coverage and errors could not enter our final product. In our team we cooperated with an open culture to prevent frustrations. We made agreements on work hours and software methodologies. Still, we faced challenges which ranged from underestimating time needed for certain features to an increasing complexity of code and data gathering. The final product is a web application which can be accessed offline. This application can be successfully used to create missions for Autonomous Underwater Vehicles, which we showed in our final usability evaluation. The LOBSTER team will be using our product to plan their missions in the future. However, before it can be fully used, the low-level control software of the LOBSTER robots needs to be finished by the LOBSTER team.