e53a0a2978c28872a4505bdb51db06dc-Reviews.html

The paper intends to unify several previously-achieved characteristics of movement primitives (MP) in a single probabilistic framework, while also describing new ways in which this framework allows MPs to be modified or combined. This is accomplished through the representation of trajectories by probability distributions of joint location and velocity. The authors present the foundation for their formulation by describing how standard MP features such as rhythmic and stroke-based movements and temporal modulation are achieved in this new framework. They also discuss how, due to the probabilistic nature of this framework, they can modify position and velocity of a given trajectory through conditioning as well as blend multiple MPs together by multiplying distributions. The authors derive the necessary values for a robotic controller and conclude the paper with experiments on both a real and simulated robotic arm.