Dynamical movement primitives (DMPs) are one of the most popular representations for goal-directed motion primitives in robotics. They are also often used as the policy representation for policy improvement in robotics, a particular form of reinforcement learning. dmpbbo provides five software modules for the representation and optimization of dynamical movement primitives
Movement Primitives (MPs) are a promising way for representing robot motions in a flexible and adapt...
In this work, we propose an augmentation to the Dynamic Movement Primitives (DMP) framework which al...
Biological systems, including human beings, have the innate ability to perform complex tasks in vers...
C++ library for Function Approximation, Dynamical Movement Primitives, and Black-Box Optimizatio
Dynamic Movement Primitives (DMPs) provide a means for parameterizing point-to-point motion. They ha...
This paper discusses a comprehensive framework for modular motor control based on a recently develop...
The concept of dynamical movement primitives (DMPs) has become popular for modeling of motion, commo...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
AbstractThe problem of movement coordination in large DoF (Degree of Freedom) robots is complex due ...
Dynamic Movement Primitives (DMPs) is a framework for learning a point-to-point trajectory from a de...
Learning from demonstration becomes increasingly popular as an efficient way of robot programming. N...
In this paper, it is shown that temporally coupled dynamical movement primitives (DMPs), used to mod...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Dynamic Motion Primitives (DMPs) only address the generalization problem for target positions that a...
We formalize the problem of adapting a demonstrated trajectory to a new start and goal configuration...
Movement Primitives (MPs) are a promising way for representing robot motions in a flexible and adapt...
In this work, we propose an augmentation to the Dynamic Movement Primitives (DMP) framework which al...
Biological systems, including human beings, have the innate ability to perform complex tasks in vers...
C++ library for Function Approximation, Dynamical Movement Primitives, and Black-Box Optimizatio
Dynamic Movement Primitives (DMPs) provide a means for parameterizing point-to-point motion. They ha...
This paper discusses a comprehensive framework for modular motor control based on a recently develop...
The concept of dynamical movement primitives (DMPs) has become popular for modeling of motion, commo...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
AbstractThe problem of movement coordination in large DoF (Degree of Freedom) robots is complex due ...
Dynamic Movement Primitives (DMPs) is a framework for learning a point-to-point trajectory from a de...
Learning from demonstration becomes increasingly popular as an efficient way of robot programming. N...
In this paper, it is shown that temporally coupled dynamical movement primitives (DMPs), used to mod...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Dynamic Motion Primitives (DMPs) only address the generalization problem for target positions that a...
We formalize the problem of adapting a demonstrated trajectory to a new start and goal configuration...
Movement Primitives (MPs) are a promising way for representing robot motions in a flexible and adapt...
In this work, we propose an augmentation to the Dynamic Movement Primitives (DMP) framework which al...
Biological systems, including human beings, have the innate ability to perform complex tasks in vers...