Knowledge Sharing in Heterogeneous Teams
My proposal topic involves the sharing of knowledge and experiences among heterogeneous robots with differing perceptual and motor capabilities.
Towards this goal, the first paper we have published involves proposing to leverage similarity to deal with heterogeneity. Specifically, we show how establishing a physically shared context can be used to learn models of the differences between two robots. This is similar to the joint attention or gaze following subfields, but in this case the purpose is to ensure a shared context in order to figure out perception differences arising from robot heterogeneity. In the paper, we analyzed the cost and accuracy of several methods for the establishment of the physically shared context with respect to such modeling.