Virtual Operator Modeling Approach for Construction Machinery

Thumbnail Image
Date
2015-01-01
Authors
Du, Yu
Anderson, Eric
Kane, Lawrence
Gilmore, Brian
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Person
Dorneich, Michael
Professor
Person
Steward, Brian
Professor
Research Projects
Organizational Units
Organizational Unit
Industrial and Manufacturing Systems Engineering
The Department of Industrial and Manufacturing Systems Engineering teaches the design, analysis, and improvement of the systems and processes in manufacturing, consulting, and service industries by application of the principles of engineering. The Department of General Engineering was formed in 1929. In 1956 its name changed to Department of Industrial Engineering. In 1989 its name changed to the Department of Industrial and Manufacturing Systems Engineering.
Organizational Unit
Agricultural and Biosystems Engineering

Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.

History
In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.

Dates of Existence
1905–present

Historical Names

  • Department of Agricultural Engineering (1907–1990)

Related Units

Journal Issue
Is Version Of
Versions
Series
Abstract

Greater understanding of how highly skilled operators achieve high machine performance and productivity can inform the development of automation technology for construction machinery. Current human operator models, however, have limited fidelity and may not be useful for machinery automation. In addition, while physical modeling and simulation is widely employed in product development, current operator simulation models may be a limiting factor in assessing the performance envelope of virtual prototypes. A virtual operator modelling approach for construction machinery was developed. Challenges to the development of human operator models include determining what cues and triggers human operators use, how human operators make decisions, and how to account for the diversity of human operator responses. Operator interviews were conducted to understand and build a framework of tasks, strategies, cues, and triggers that operators commonly use while controlling a machine through a repeating work cycle. In particular, a set of operation data were collected during an excavator trenching operation and were analyzed to classify tasks and strategies. A rule base was derived from interview and data analyses. Common nomenclature was defined and is explained. Standard tasks were derived from operator interviews, which led to the development of task classification rules and algorithm. Task transitions were detected with fuzzy transition detection classifiers.

Comments

This is a paper from Proceedings of the 2015 Conference on Autonomous and Robotic Construction of Infrastructure, which can be found in full at: http://lib.dr.iastate.edu/intrans_reports/141/.

Description
Keywords
Citation
DOI
Source
Copyright
Thu Jan 01 00:00:00 UTC 2015