Dimensionality Reduction in Learning Gaussian Mixture Models of Movement Primitives for Contextualized Action Selection and Adaptation

Robotic manipulation often requires adaptation to changing environments. Such changes can be represented by a certain number of contextual variables that may be observed or sensed in different manners. When learning and representing robot motion-usually with movement primitives, it is desirable to adapt the learned behaviors to the current context. Moreover, different actions or motions can be considered in the same framework, using...