Manifold Relevance Determination: Learning the Latent Space of Robotics

In this article we present the basics of manifold relevance determination (MRD) as introduced in [Damianou et al., 2012], and some applications where the technology might be of particular use. Section 1 acts as a short tutorial of the ideas developed in [Damianou et al., 2012], while Section 2 presents possible applications in sensor fusion, multi-agent SLAM, and “humanappropriate” robot movement (e.g. legibility and predictability [Dragan et al., 2013]). In particular, we show how MRD can be used to construct the underlying models in a data driven manner, rather than directly leveraging first principles theories (e.g., physics, psychology) as is commonly the case for sensor fusion, SLAM, and human robot interaction.