How do we make a machine that indicates changes to its internal state, e.g., goals, attitude, or even emotion, through changes in movement profiles? That is, how do we build a machine that is fluent in body-language? This workshop will pose a possible direction toward such ends that leverages movement notation as a source for clearly defining abstract concepts of similarity and symbolic representation of the parts and patterns of movement – in order to identify, record, and interpret patterns of human movement on both the micro and macro levels.
First, we will move together. This will activate an innate ability to imitate each other and, in doing so, illuminate the principal components of Laban/Bartenieff Movement Studies and the Body, Effort, Shape, Space, and Time (BESST) System of movement analysis.
Next, we will try to write down what we’re doing. A set of symbols for describing elements of the BESST System, which seem to be particularly perceptually meaningful to human observers, will be presented so that movement ideas can be notated and, thus, translated between bodies.
A keynote talk frames the material of the tutorial for broader arts-based research in robotics. This workshop is supported by NSF award #2234196.
