Engineering Optimal Gesture Sets for UAVs

Typically, a user controls the flight of a UAV using either a standard off-the-shelf remote controller or a touchscreen-based device. In view of the potential introduction of UAVs into our daily life, we focus on “natural” user interfaces that are fast to learn and easy to use, particularly, employing natural modalities such as speech, gestures, and gaze direction. For such modalities, we consider the design of natural and intuitive input vocabularies an important issue which we discuss using gestures as the specific modality under analysis.

Standard procedures to come up with a gesture vocabulary are typically based on the majority principle (i.e., using gestures most frequently suggested by users). While these procedures aim for “good” individual gestures, they do not take into account the quality of the resulting gesture set as a whole. We investigate our hypothesis that more coherent gesture sets (vocabularies) are more intuitive than less coherent ones, where “coherent” means that the elements of the set are associated with as few as possible underlying mental models – ideally with only a single one. For a coherent gesture set, a single hint gesture may suffice to enable the user to guess (and subsequently memorize) the remaining ones.

Since our experiments support this hypothesis, we suggest a measure for this specific quality and describe user centered procedures to design highly coherent gesture sets.