Biological systems, including human beings, have the innate ability to perform complex
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …

Task-parameterized models of movements aim at automatically adapting movements to new
situations encountered by a robot. The task parameters can, for example, take the form of …

Movement Primitives are a well-established paradigm for modular movement representation
and generation. They provide a data-driven representation of movements and support …

The framework of dynamic movement primitives (DMPs) contains many favorable properties
for the execution of robotic trajectories, such as indirect dependence on time, response to …

Task-parameterized skill learning aims at adaptive motion encoding to new situations. While
existing approaches for task-parameterized skill learning have demonstrated good …

In this paper, we address the problem of simultaneously achieving low trajectory tracking
errors and compliant control without using explicit mathematical models of task dynamics. To …

Gestures are characterized by intermediary or final landmarks (real or virtual) in task space
or joint space that can change during the course of the motion, and that are described by …

作为机器人技能学习中的一个重要分支, 模仿学习近年来在机器人系统中得到了广泛的应用.
模仿学习能够将人类的技能以一种相对直接的方式迁移到机器人系统中, 其思路是先从少量示教 …

Just like humans, robots can improve their performance by practicing, ie by performing the
desired behavior many times and updating the underlying skill representation using the …

Robots that can learn over time by interacting with non-technical users must be capable of
acquiring new motor skills, incrementally. The problem then is deciding when to teach the …