In this work, a novel Dynamic Movement Primitive (DMP) formulation is proposed which supports reversibility, i.e. backwards reproduction of a learned trajectory. Apart from sharing all favourable properties of the original DMP, decoupling the teaching of position and velocity profiles and bidirectional drivability along the encoded path are also supported. Original DMP have been extensively used for encoding and reproducing a desired motion pattern in several robotic applications. However, they lack reversibility, which is a useful and expedient property that can be leveraged in many scenarios. The proposed formulation is analyzed theoretically and its practical usefulness is showcased in an assembly by insertion experimental scenario
Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dyna...
Abstract. Learning to perform complex tasks out of a sequence of sim-ple small demonstrations is a k...
Dynamic movement primitives (DMP) are an efficient way for learning and reproducing complex robot be...
The concept of dynamical movement primitives (DMPs) has become popular for modeling of motion, commo...
This paper presents a novel trajectory generator based on Dynamic Movement Primitives (DMP). The k...
This paper presents a novel trajectory generator based on Dynamic Movement Prim-itives (DMP). The ke...
This paper discusses a comprehensive framework for modular motor control based on a recently develop...
Book Series: IEEE International Conference on Robotics and Automation ICRA. ISSN: 1050-4729This pape...
The generation of complex movement patterns, in particular in cases where one needs to smoothly and ...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Dynamic Movement Primitives (DMPs) provide a means for parameterizing point-to-point motion. They ha...
Dynamic Movement Primitives (DMPs) is a framework for learning a point-to-point trajectory from a de...
Abstract — Dynamic Movement Primitives (DMP) are nowa-days widely used as movement parametrization f...
Abstract—In this paper, we propose a novel concept of move-ment primitives called Stylistic Dynamic ...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dyna...
Abstract. Learning to perform complex tasks out of a sequence of sim-ple small demonstrations is a k...
Dynamic movement primitives (DMP) are an efficient way for learning and reproducing complex robot be...
The concept of dynamical movement primitives (DMPs) has become popular for modeling of motion, commo...
This paper presents a novel trajectory generator based on Dynamic Movement Primitives (DMP). The k...
This paper presents a novel trajectory generator based on Dynamic Movement Prim-itives (DMP). The ke...
This paper discusses a comprehensive framework for modular motor control based on a recently develop...
Book Series: IEEE International Conference on Robotics and Automation ICRA. ISSN: 1050-4729This pape...
The generation of complex movement patterns, in particular in cases where one needs to smoothly and ...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Dynamic Movement Primitives (DMPs) provide a means for parameterizing point-to-point motion. They ha...
Dynamic Movement Primitives (DMPs) is a framework for learning a point-to-point trajectory from a de...
Abstract — Dynamic Movement Primitives (DMP) are nowa-days widely used as movement parametrization f...
Abstract—In this paper, we propose a novel concept of move-ment primitives called Stylistic Dynamic ...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dyna...
Abstract. Learning to perform complex tasks out of a sequence of sim-ple small demonstrations is a k...
Dynamic movement primitives (DMP) are an efficient way for learning and reproducing complex robot be...