An Evaluation of Affordance Templates for Human-Robot Interaction

There is an interest in and need for the use of semiautonomous robots in various fields, such as disaster response. Over the years, different techniques for semiautonomous control were developed, ranging from teleoperation guidance to different user interface designs for setting task constraints and goals interactively. Among those, affordance templates emerged as a recent method for users to efficiently provide robots with contextual information about object shapes, properties, and affordances. In many fields where direct teleoperation is common, affordance templates seem to be a promising candidate for improving performance and usability. However, despite the reports on the potential benefits of this technique in comparison to direct teleoperation, they are often qualitative or focus on tasks where teleoperation is particularly challenging. This can be a problem because task difficulty can influence different performance metrics and human factors, so results from studies that show large differences in task difficulty between interaction modes cannot be directly generalized to tasks with smaller or non-existent differences in difficulty. In this study, we aim to evaluate the effectiveness of affordance templates in the context of debris removal for disaster response, a task where direct teleoperation is a viable technique. We compared the two methods in a simulated setting through a user study involving 41 participants by measuring a) usability through questionnaires and b) performance on secondary tasks, an established measure of spare information processing capacity. The study results show that despite similar difficulty, users performed better on secondary tasks when using affordance template-based semiautonomy in this setting.