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Statistical identification and macroscopic transitional model between disorder and order

Research output: Chapter in Book/Report/Conference proceedingConference paper

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
Publication statusPublished - 22 Sep 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: 31 May 20147 Jun 2014


Conference2014 IEEE International Conference on Robotics and Automation, ICRA 2014
CityHong Kong

King's Authors


Food processing provides a lot of possibilities to apply robotics and automation. In this paper, we identify disordered and ordered states of discrete food products. The concept of Degree of Disarray is introduced. Food ordering processes such as vibratory feeders, multi-head weighers, pick and place operations are common automation in food industry to transfer products from a higher to a lower Degree of Disarray. Parts entropy is introduced to describe a product's individual state based on the symmetry categorisation. A macroscopic transitional model is presented which determines a subspace of the disordered arrangement using the eigenvectors of the largest eigenvalues of the covariance matrix. A projection into this created subspace follows. As soon as the disorder state in only one dimension is achieved, the point of disorder can be derived which finally transfers the objects into order. From here, a transformation to any order arrangement in any dimension is possible. This methodology is applied to pick and place operations and experiments are conducted.

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