Towards a real time simulation of Linked Multi-Component Robotic Systems

被引：2

作者：

Manuel Lopez-Guede, Jose ^{[1
]}

Fernandez-Gauna, Borja ^{[2
]}

Zulueta, Ekaitz ^{[1
]}

机构：

[1] Basque Country Univ UPV EHU, Univ Coll Engn Vitoria, Dept Syst Engn & Automat Control, Nieves Cano 12, Vitoria 01006, Spain

[2] Univ Basque Country, Grp Inteligencia Computac, E-48080 Bilbao, Spain

来源：

ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS | 2012年 / 243卷

关键词：

Linked Multicomponent Robotic Systems; Q-Learning; Reinforcement Learning; Hose Control; Geometrically Exact Dynamic Splines;

D O I：

10.3233/978-1-61499-105-2-2019

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The autonomous behavior learning in Linked Multicomponent Robotic Systems is an open issue. Single Robot Hose Transport is a limit case of this kind of systems, when one robot moves the tip of the hose to a desired position. The interaction between the passive, flexible hose and the robot introduces highly non-linear effects in the system's dynamics thus making necessary the utilization of accurate geometrical and dynamical models. This paper reports the computational requirements that we have found using these models in a Reinforcement Learning framework and we address a possible solution to mitigate them.

引用

页码：2019 / 2027

页数：9

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