… and human-robot interaction. In section 4, we describe the development of a generative
model through observation of people playing shadow puppets aimed at enabling our robot to …

… we can teach about generative models before we introduce … and applications of generative
modeling techniques, and what … Though students were exposed to indicators of manipulated …

… generative model for trajectories, that learns to segment raw trajectories into reoccurring
patterns (subtasks) and the individual skills … the required skills for such manipulation tasks, than …

… generative model for autonomous robotics. It enables context-sensitive, robust task abilities
… sequence and coordination of locomotion and manipulation skills, we designed a task that …

… algorithms and generative models to learn representations of the world and accomplish
challenging manipulation tasks efficiently. Our work is a step towards robotic agents that bridge …

… We describe a formalization of the robot manipulation learning problem that synthesizes
existing research into a single coherent framework and highlight the many remaining research …

… Our work joins a number of recent papers that focus on learning robotic manipulation using
… -supervised learning with generative models [36] where they use a generative model via the …

… This paper proposed a deep belief neural network-based generative model for detection of
robotic manipulator’s failure execution. A deep theoretical as well as the practical scheme is …

… into essential skills or reusable knowledge. For exploiting such benefits also in robotic
manipulation, we propose an unsupervised method for transferable manipulation skill discovery …

… generative model (OCGM) [12] for versatile, one-shot goal identification and re-identification
as a key component in solving complex manipulation … space of a robot manipulator from a …