PeriSim: A Simulator for Optimizing Peristaltic Table Control

Peristaltic conveyance can be used for the sorting and transport of delicate and nonrigid objects such as meat or soft fruit. The non‐linearity and stochastic behavior of peristaltic systems make them difficult to control. Optimizing controllers using machine learning represents a promising path to...

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Bibliographic Details
Published in:Advanced intelligent systems 2019-12, Vol.1 (8), p.n/a
Main Authors: McKenzie, Ross M., Roberts, Jamie O., Sayed, Mohammed E., Stokes, Adam A.
Format: Article
Language:English
Subjects:
modular robotics
object conveyance
peristaltic systems
sorting
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Summary:Peristaltic conveyance can be used for the sorting and transport of delicate and nonrigid objects such as meat or soft fruit. The non‐linearity and stochastic behavior of peristaltic systems make them difficult to control. Optimizing controllers using machine learning represents a promising path to effective peristaltic control but currently, there is no suitable simulated model of a peristaltic table in which to run these optimizations. A simple, simulated model of a peristaltic conveyor that can be used for optimizing peristaltic control on a variety of peristaltic tables is presented. This simulator is demonstrated through a limited control problem evaluated on our real‐world system that is built for peristaltic conveyance. This simulator is available as the python package PeriSim so that it can be used by the robotics community for peristaltic control development. Peristaltic sorting tables are robotic systems that use a deformable surface to control the position of objects via sliding or rolling. These systems can manipulate objects that are difficult to move on existing 2D conveyors. In this work, the peristaltic table simulator, PeriSim, is presented and experimentally validated. This simulator will be useful for any research into peristaltic control strategies.
ISSN:2640-4567
2640-4567
DOI:10.1002/aisy.201900070