Sensing in Advanced Robotic Assembly

Abstract

Sensors are typically added to programmable assembly cells in order to enable correct operation when components are imprecisely positioned, and when fixtures, actuators and other cell resources are non-ideal. The assembly operation and the environment can be monitored so that any errors can be detected and recovery actions can be selected automatically. In an ideal world the synthesis of such a system for a given assembly problem would be simple, quick to undertake and foolproof. Such systems could then be applied to rapidly changing small-batch production environments. However, in practice, the synthesis of sensory assembly systems is non-trivial, time-consuming and error prone. The paper categorizes the use of sensors in assembly with illustrations from practical assembly projects. This then leads to ideas about sensor selection and how sensory information can be used in decision-making. An outline is given of a probabilistic framework which can be used as a basis for both of these tasks.

Keywords

Robots sensors assembly automation

Get full access to this article

View all access options for this article.

References

Durrant-Whyte

H F

(1988), Integration, Co-ordination and Control of Multisensor Robot Systems Kluwer Academic Publishers.

Fikes

R E

Hart

P E

Nilsson

(1972) ‘Some new directions in problem solving’, Machine Intelligence 3, 405–430.

Kemp

D R

(1983) ‘A prototype robot workstation for the motif application process within the garment manufacturing industry’. Proc. 2nd IASTED Int. Symp. on Robotics and Automation..

Kemp

D R

Taylor

G E

Taylor

P M

Pugh

(1986) ‘A sensory gripper for handling textiles’ in Pham

D T

Heginbotham

W B

Robot Grippers 155–164. IFS (Publications).

Kamel

M S

(1988) ‘Representing uncertainty in robot task planning’. Proc. IEEE Conf. on Robotics and Automation, 1728–1734.

Munson

J H

(1971) ‘Robot planning, execution and monitoring in an uncertain environment’, Proc. Second IJCAI, 338.

Pugh

Heginbotham

W B

Kitchen

P W

Page

C J

Gatehouse

D O

(1973) ‘The Nottingham SIRCH assembly robot’. Proc. Conference on Shop Floor Automation. NEL, East Kilbride.

Monkman

Taylor

G E

Taylor

P M

(1989) ‘Flowgraph techniques in workcell assessment and design’. Proc. IEEE Int. Symp. on Intelligent Control. 28–32.

Ravini

, (Ed) (1988) CAD-Based Programming for Sensor-based Robots, NATO ASI Series F. Vol. 50. Springer-Verlag.

10.

Sacer

S E D

(1975) A structure for plans and behavior, Tech Note 109. AI Center, SRI International.

11.

Saridis

, (Ed) Knowledge-based Robotic Control, NATO ASI Series F. Springer-Verlag. To be published 1989/90.

12.

Selke

K K W

Swift

K G

Taylor

G E

Pugh

Davey

S N

Deacon

G E

(1987) ‘Knowledge based robotic assembly — a step towards flexibility’. Computer Aided Engineering Journal. 62–67.

13.

Taylor

G E

Taylor

P M

Monkman

E-Zadeh

(1988a) ‘Automated inspection of shirt collars’. Proc. RoViSeC-7..

14.

Taylor

G E

Taylor

P M

(1988b) ‘Dynamic error probability vectors: a framework for sensory decision making’. Proc. IEEE Conf. on Robotics and Automation. 1096–1100.

15.

Taylor

P M

Selke

K K W

Pugh

(1983) ‘Visual feedback applied to the assembly of thyristors’. Proc. Congres AFCET Automatique, Productique et Robotique Intelligente, 151–162.

16.

Taylor

P M

Halleron

Song

X-K

(1989) ‘The application of a dynamic error framework to robotic assembly’. Internal report, University of Hull, submitted for publication..

17.

Zhou

DiCesare

Desrochers

A A

(1989) ‘A top-down approach to systematic synthesis of Petri net models for manufacturing systems’. Proc. IEEE Conf. on Robotics and Automation. 534–539.