PhD Research Positions available, Nottingham England

[chandler]

VACANCIES

Research (2 Bursary Students)

Object Recognition for Assembly

Human Centred Assembly

Introduction

The Manufacturing Automation Research Group (MARG) has been working on the
development of Artificial Intelligence techniques for the recognition of 3-D
objects. The aim of this work is to develop a system for the recognition of
solid objects independent of their position and orientation within the work
domain. This is to aid in the manipulation of objects within a robotic cell,
particularly for the processes of assembly and other manipulative tasks . In
the formation of this work, a novel method using ANN with parallels
to the processing within the primate visual system, has been used.

The Programme

Object Recognition for Assembly The aim of this project is to improve the
fundamental understanding of object recognition for use in assembly process.
The major area of the research will be the implementation of novel
techniques of object recognition, and provide position and rotation
parameters to enable assembly tasks to be executed. The ANN techniques already
developed in-house will be extended and integrated with the robot, providing
invariant object recognition capability to the system. Additionally the
geometric descriptors will be assessed for their validity/accuracy. Task
level robotic operations can then use these descriptors as a base for
further actions.

Human Centred Assembly

Whilst the sections of the research programme described above will provide
both novel and effective robotic assembly, this section of the work seeks to
draw the maximum knowledge from existing manual methods. It therefore
provides an effective link, drawing knowledge from the manual operation and
contributing to the learning of a manipulative skill by a machine. The work
will analyse human centred assembly strategies and contrast them with
automation techniques. Methods which are applicable to sensory challenged
human assembly will be interpreted and applied to the sensor equipped robot.

Applications invited from Graduates (Engineering, Science) with good
classifications
Bursary  6,000 UKP / annum for 3 years
Applicants will be expected to register for a PhD programme.

References

1) Keat J, Balendran V, Sivayoganathan K. 1995. Invariant Object Recognition
with a Neurobiological Slant, Proceeding of the Fourth IEE International
Conference on Artificial Neural Networks, Cambridge.

2) Keat J, Balendran V, Sivayoganathan K, Sackfield A. "IvOR: A 
Neurobiologically slanted approach to PSRI Object recognition", 5th Irish 
Neural Network Conference - INNC95, September 11-13, 1995, pp. 30-37, 
Maynooth, Ireland.

3) Howarth M, Sivayoganathan K, Thomas P, Gentle C.R., "Robotic task level 
programming using neural networks", 4th Int. Conf.on Artificial Neural 
Networks, 26-28 June 1995. pp 262-267. Churchill College, Cambridge.

4) Balendran V, Sivayoganathan K, Al-Dabass D. 1989. Detection of flaws on
slowly varying surfaces, Proceedings of the Fifth National Conference on
Production Research, London, Kogan Press, pp82-85.

5) Keat J, Balendran V, Sivayoganathan K, Sackfield A. 1994. 3-D data
collection for object recognition, Advances in Manufacturing Technology
VIII, Proceedings of the Tenth National Conference on Manufacturing
Research, Loughborough, pp648-652.


Contact:

Dr. K. Sivayoganathan
		man3sivayk at ntu.ac.uk 	  tel: +44(0)115 941 8418 ex 4112.
Dr. S. Kennedy 	man3kennesj at ntu.ac.uk 	  tel: +44(0)115 941 8418 ex 4106.
Mr. M. Howarth 	m.howarth at marg.ntu.ac.uk  tel: +44(0)115 941 8418 ex 4110.

Manufacturing Automation Research Group
Department of Manufacturing Engineering,
Burton Street,
Nottingham,
NG1 4BU.
fax: +44(0)115 941 4024