King's College London

Research portal

A Library for Constraint Consistent Learning

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalAdvanced Robotics
Early online date7 Jul 2020
DOIs
Publication statusE-pub ahead of print - 7 Jul 2020

Documents

King's Authors

Abstract

This paper introduces the first, open source software library for Constraint Consistent Learning (CCL). It implements a family of data-driven methods that are capable of (i) learning state-independent and -dependent constraints, (ii) decomposing the behaviour of redundant systems into task- and null-space parts, and (iii) uncovering the underlying null space control policy. It is a tool to analyse and decompose many everyday tasks, such as wiping, reaching and drawing. The library also includes several tutorials that demonstrate its use with both simulated and real world data in a systematic way. This paper documents the methods contained within the library, including the implementations of said methods in tutorials and associated helper methods. The software is made freely available to the community, to enable code reuse and allow users to gain in-depth experience in statistical learning in this area.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454