Learning control for space robotic operation using support vector machines

Panfeng Huang, Wenfu Xu, Yangsheng Xu, Bin Liang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Automatical operation of space robots is a challenging and ultimate goal of space servicing. In this paper, we present a novel approach for tracking and catching operation of space robots based on learning and transferring human control strategies (HCS). We firstly use an efficient support vector machine (SVM) to parameterize the model of HCS, and then develop a new SVM-based leaning structure to improve HCS in tracking and capturing control. The approach is fundamentally valuable in dealing with some problems such as small sample data and local minima, which makes it efficient in modeling, understanding and transferring its learning process. The simulation results demonstrate that the proposed method is useful and feasible in tracking trajectory and catching objects autonomously.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2006
Subtitle of host publicationThird International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II
PublisherSpringer Verlag
Pages1208-1217
Number of pages10
ISBN (Print)3540344373, 9783540344377
DOIs
StatePublished - 2006
Event3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks - Chengdu, China
Duration: 28 May 20061 Jun 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3972 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks
Country/TerritoryChina
CityChengdu
Period28/05/061/06/06

Fingerprint

Dive into the research topics of 'Learning control for space robotic operation using support vector machines'. Together they form a unique fingerprint.

Cite this