A Reversible Dynamic Movement Primitive formulation

10/15/2020
by   Antonis Sidiropoulos, et al.
0

In this work, a novel Dynamic Movement Primitive (DMP) formulation is proposed which supports reversibility, i.e. backwards reproduction of a learned trajectory, while also sharing all favourable properties of classical DMP. Classical 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 is validated through simulations and experiments.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/25/2022

Certifying algorithms and relevant properties of Reversible Primitive Permutations with Lean

Reversible Primitive Permutations (RPP) are recursively defined function...
research
10/29/2021

Stitching Dynamic Movement Primitives and Image-based Visual Servo Control

Utilizing perception for feedback control in combination with Dynamic Mo...
research
05/11/2018

Learning Movement Assessment Primitives for Force Interaction Skills

We present a novel, reusable and task-agnostic primitive for assessing t...
research
12/27/2022

Efficient DMP generalization to time-varying targets, external signals and via-points

Dynamic Movement Primitives (DMP) have found remarkable applicability an...
research
07/11/2023

Deep Probabilistic Movement Primitives with a Bayesian Aggregator

Movement primitives are trainable parametric models that reproduce robot...
research
09/18/2022

A Non-parametric Skill Representation with Soft Null Space Projectors for Fast Generalization

Over the last two decades, the robotics community witnessed the emergenc...
research
04/06/2022

Perceive, Represent, Generate: Translating Multimodal Information to Robotic Motion Trajectories

We present Perceive-Represent-Generate (PRG), a novel three-stage framew...

Please sign up or login with your details

Forgot password? Click here to reset