The video game industry, while refining hardware, techniques, graphics technology, and software, produce a variety of interfaces for controlling and representing the virtual worlds they present. This feedback and controls convey control of a world analogous to the real world, with interactions helping the player effect that world. These methods used in games can be translated usefully for controlling robotic platforms in the real world. The amount of robots used in the field for military, commercial, and disaster response increases every year. Using games as inspiration, these robot systems can be improved to produce more efficient interfaces, utilize mass-produced commodity hardware, and reduce training time with operators increasingly familiar with these types of control. This dissertation proposes a method for transferring game interactions to robotic interfaces. The method works in five stages: identifying the task as a common robot task, choosing a game interaction and describing it, translating elements to robotic interface requirements, developing interfaces using these mappings, and testing the resulting interfaces to determine the impact of the changes. To help researchers use the method, a survey of common game interactions are identified from recent popular games and described for the second stage of the method. A framework for remote robot interaction studies was developed and is presented, using a client-server architecture enable participants in a robot interface user study to simulate robots and submit study results. This framework provides many advantages over a traditional in-person user study. Four robot interfaces are developed using the method, tested using a variety of evaluation methods. The first uses GPS and planning to command multiple robots, tested through experimental trials and three scenarios. The second studies selection and formation movement techniques when interacting with multiple robots, using the remote study framework for testing. The third also uses the remote study framework, focusing on adding a queue of future actions to a supervisory control interface. The last interface uses augmented reality in a teleoperation interface to show a virtual trail of previously visited locations. This interface was validated through a usability study with a mobile robot exploration task, showing significant improvement in efficiency.