Atlantis Press Paper Details: Towards Automated Code Generation for Autonomous Mobile Robots

With the expected growth in mobile robotics the demand for expertise to develop robot control code will also increase. As end-users cannot be expected to develop this control code themselves, a more elegant solution would be to allow the end-users to teach the robot by demonstrating the task. In this paper we show how route learning tasks may be ¨translated¨ directly into robot control code simply by observing the task. We show how automated code generation may be facilitated through system identification which algorithmically and automatically transfers human behaviour into control code, using transparent mathematical functions. We provide two route learning examples where a mobile robot automatically obtains control code simply by observing human behaviour, identifying it using system identification, and copying the behaviour.


title:		Towards Automated Code Generation for Autonomous Mobile Robots
publication:		AGI-10
part of series:		Advances in Intelligent Systems Research
ISBN:		978-90-78677-36-9
ISSN:		1951-6851
DOI:		doi:10.2991/agi.2010.37 (how to use a DOI)
author(s):		D. Kerr, U. Nehmzow, S.A. Billings
publication date:		March 2010
abstract:		With the expected growth in mobile robotics the demand for expertise to develop robot control code will also increase. As end-users cannot be expected to develop this control code themselves, a more elegant solution would be to allow the end-users to teach the robot by demonstrating the task. In this paper we show how route learning tasks may be ¨translated¨ directly into robot control code simply by observing the task. We show how automated code generation may be facilitated through system identification which algorithmically and automatically transfers human behaviour into control code, using transparent mathematical functions. We provide two route learning examples where a mobile robot automatically obtains control code simply by observing human behaviour, identifying it using system identification, and copying the behaviour.
copyright:		© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
full text:		AGI-10-paper_055.pdf (451 K)