Learning from demonstration (LfD) has been used to help robots to implement manipulation
tasks autonomously, in particular, to learn manipulation behaviors from observing the motion …

With the rapid advancement of manufacturing in China, robot machining technology has
become a popular research subject. An increasing number of robots are currently being …

We present a three-level cognitive system in a learning by demonstration context. The
system allows for learning and transfer on the sensorimotor level as well as the planning …

Autonomy is increasingly demanded to industrial manipulators. Robots have to be capable
to regulate their behavior to different operational conditions, adapting to the specific task to …

Programming by demonstration is reaching industrial applications, which allows non-experts
to teach new tasks without manual code writing. However, a certain level of complexity, such …

We present a new interaction paradigm for robot learning from demonstration, called
simultaneous learning of hierarchy and primitives (SLHAP), in which information about …

We propose a framework based on imitation learning and self-learning to enable robots to
learn, improve, and generalize motor skills. The peg-in-hole task is important in …

Virtual guiding fixtures constrain the movements of a robot to task-relevant trajectories, and
have been successfully applied to, for instance, surgical and manufacturing tasks. Whereas …

Learning from demonstration (LfD) seeks to democratize robotics by enabling non-experts to
intuitively program robots to perform novel skills through human task demonstration. Yet, LfD …

In human-robot comanipulation, virtual guides are an important tool used to assist the
human worker by reducing physical effort and cognitive overload during tasks …