Project
The Danish meat industry is caught in an unfortunate trend where the number of pigs being slaughtered domestically is decreasing, while pigs exported for finishing and slaughter is increasing. This threatens the critical mass needed to maintain the few remaining domestic slaughterhouses. Only by transitioning to a more intelligent and flexible automation paradigm will it be possible to maintain this important domestic industry. The central problem with slaughterhouse automation is coping with the biological variation that is inherent to the setting. This project addresses this problem through a combination of advanced sensors and machine learning.
Scientific Work
PhD Thesis: Link to thesis
Cutting Pose Prediction from Point Clouds
Philipsen, M. P. & Moeslund, T. B.,
11 Mar 2020, In: Sensors. 20, 6, 22 p., 1563.
Intelligent Injection Curing of Bacon
Philipsen, M. P. & Moeslund, T. B.,
2019, In: Procedia Manufacturing. 38, p. 148-155
Industrial Human-Robot Collaboration
Philipsen, M. P., Rehm, M. & Moeslund, T. B.,
Jul 2018, Proc. FAIM/ISCA Workshop on Artificial Intelligence for Multimodal Human Robot Interaction. p. 35-38
Organ Segmentation in Poultry Viscera Using RGB-D
Philipsen, M. P., Dueholm, J. V., Jørgensen, A., Escalera, S. & Moeslund, T. B.,
3 Jan 2018, In: Sensors. 18, 1, 15 p., 117.
Funding
This Industrial PhD is a collaboration with Danish Technological Institut, funded by Innovation Fund Denmark under the grant number: 5189-00116B.
Contact
PhD Fellow: Mark Philip Philipsen
Mail: mpph@create.aau.dk
Supervisor: Thomas B. Moeslund
Mail: tbm@create.aau.dk
