ISSN:
1433-3015
Keywords:
Autonomous robotic systems
;
Automatic error recovery
;
Automatic assembly process
;
Error identification tree
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
Abstract Successful automatic assembly of complex artefacts requires the robotic system to have the capability of detecting, identifying and recovering from various errors. Efficient error identification process is essential to ensure fast recovery and minimum loss of production time. It is not cost-effective to interrogate every sensor for every pass through the assembly process. This paper presents a machine-learning approach to identify error. The basic idea is to construct a decision tree based on some sensor and error attributes in the knowledge base.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01751099
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