PRF: A Program Reuse Framework for Automated Programming by Learning from Existing Robot Programs

This paper explores the problem of automated robot program generation from limited historical data when neither accurate geometric environmental models nor online vision feedback are available. The Program Reuse Framework (PRF) is developed, which uses expert-defined motion classes, a novel data str...

Full description

Saved in:
Bibliographic Details
Published in:Robotics (Basel) Vol. 13; no. 8; p. 118
Main Authors: Toner, Tyler, Tilbury, Dawn M., Barton, Kira
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.08.2024
Subjects:
automated programming
Automation
Data structures
Datasets
Deep learning
Design
End effectors
Environment models
Historical structures
learning from demonstration (LfD)
Libraries
Manipulators
Python
Redundancy
redundant manipulators
Robot arms
Robot dynamics
Robots
Sensors
skill-based programming
Skills
task and motion planning
workspace learning
ISSN:2218-6581, 2218-6581
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper explores the problem of automated robot program generation from limited historical data when neither accurate geometric environmental models nor online vision feedback are available. The Program Reuse Framework (PRF) is developed, which uses expert-defined motion classes, a novel data structure introduced in this work, to learn affordances, workspaces, and skills from historical data. Historical data comprise raw robot joint trajectories and descriptions of the robot task being completed. Given new tasks, motion classes are then used again to formulate an optimization problem capable of generating new open-loop, skill-based programs to complete the tasks. To cope with a lack of geometric models, a technique to learn safe workspaces from demonstrations is developed, allowing the risk of new programs to be estimated before execution. A new learnable motion primitive for redundant manipulators is introduced, called a redundancy dynamical movement primitive, which enables new end-effector goals to be reached while mimicking the whole-arm behavior of a demonstration. A mobile manipulator part transportation task is used throughout to illustrate each step of the framework.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2218-6581
2218-6581
DOI:10.3390/robotics13080118