Fitting primitive shapes to point cloudPoint Cloud scenes is a challenging but necessary step for many roboticRobotic manipulation operations. State-of-the-art primitive fittingPrimitive Fitting methods rely on geometric shapeGeometric Shapes estimation or iterative procedures. They are often computationally complex and sensitive to algorithm parameterisation. This study tackles primitive fittingPrimitive Fitting as a parameterParameters optimisation problem, solving it using the Bees AlgorithmBees Algorithm, THE. The performance of the Bees AlgorithmBees Algorithm is evaluated on three sets of artificial scenes of varying degrees of blurriness and benchmarked against an evolutionary algorithmEvolutionary Algorithm. Experimental results proved the precision and consistency of the Bees Algorithm. Primitive fitting times were compatible with real-timeReal-Time application.


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    Title :

    Shape Recognition for Industrial Robot Manipulation with the Bees Algorithm


    Additional title:

    Springer Ser.Advanced Manufacturing


    Contributors:


    Publication date :

    2022-11-20


    Size :

    14 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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