Title:
Intelligent Cutting of the Bird Shoulder Joint

dc.contributor.author Hu, Ai-Ping
dc.contributor.author Grullon, Sergio
dc.contributor.author Zhou, Debao
dc.contributor.author Holmes, Jonathan
dc.contributor.author Holcombe, Wiley
dc.contributor.author Daley, Wayne
dc.contributor.author McMurray, Gary
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.contributor.corporatename Georgia Tech Research Institute
dc.date.accessioned 2011-10-14T15:44:55Z
dc.date.available 2011-10-14T15:44:55Z
dc.date.issued 2009
dc.description Presented at the 2009 Georgia Poultry Conference, 29-30 September 2009, Athens, Georgia. en_US
dc.description.abstract Deboning operations are one of the largest users of on-line labor in today’s poultry plants. Efforts have been made over the years to automate this function, but to date have achieved only limited success. The main difficulty in this task is its unstructured nature due to the natural variability in the sizes of birds and their deformable bodies. To increase product safety and quality, the industry is looking to robotics to help solve these problems. This research has focused on developing a new method of automating the deboning of bird front halves. If this task can be automated, the technology would naturally be extended to other cuts and trimming operations in poultry and red meat. To accomplish this goal, the project team has been working for the past four years on the development of a sensor-based intelligent cutting system. This work is based on the development of a model for the cutting of bio-materials that can be extended to the cutting of meat, tendon, ligaments, and bone. When this model is combined with data from the tendon prediction system, the nominal cutting trajectory can be established and adjusted based on the cutting model in conjunction with knowledge of the bird's anatomy. The value in accomplishing this work would be to not only reduce labor costs but also to increase the yield of breast meat and reduce/eliminate bone chips. It is estimated that an increase in yield of a single percentage point could represent several millions of dollars of additional revenue for each and every plant. Current attempts at automation of the shoulder cut impose several percentage points of yield loss in return for lower labor costs. In the manual process, while generally providing a higher yield of breast meat, the quality of the product varies dramatically based on the skill of the worker, and the labor costs are significantly higher. It is the goal of this work to develop a system that eliminates labor and consistently provides a yield similar to the best manual worker. The overall vision for this project requires the development of various technology components that will be unified into a single operational system. This includes a system to identify the initial cutting point, a system to specify the nominal cutting trajectory based on the size of that specific bird, a model to predict the location of the joint and shoulder tendons given the position/orientation of the wing tip, a mathematical model of the cutting process that allows the control system to interpret force/torque data and make intelligent motion commands to avoid cutting through the bone, and a robotic platform capable of executing these commands in real-time. en_US
dc.identifier.citation Hu, A.-P., Grullon, S., Zhou, D., Holmes, J., Holcombe, W., Daley, W., & McMurray, G. (2009). “Intelligent Cutting of the Bird Shoulder Joint”. Georgia Poultry Conference, Athens, GA, September 29-30. en_US
dc.identifier.uri http://hdl.handle.net/1853/41825
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.subject Bird anatomy en_US
dc.subject Cutting forces en_US
dc.subject Deboning en_US
dc.subject Deformation en_US
dc.subject Force control en_US
dc.subject Poultry en_US
dc.subject Robot en_US
dc.title Intelligent Cutting of the Bird Shoulder Joint en_US
dc.type Text
dc.type.genre Paper
dspace.entity.type Publication
local.contributor.corporatename Georgia Tech Research Institute (GTRI)
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
relation.isOrgUnitOfPublication 3928f3f0-0759-4b3a-aa0a-10075096fef4
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Intelligent Cutting Paper for Georgia Poultry Conference-09.pdf
Size:
448.5 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.76 KB
Format:
Item-specific license agreed upon to submission
Description: