Category: History

The Leapfrog Team

This is the final history blog in a six part series – The Leapfrog Team. If you missed part five, Gaining Acceptance, you can find it here.

Many of the original development team still work for ARANZ Geo, all adding their substantial knowledge and experience to the mix.  Many joined as students in the early days to advance the RBF mathematics and software that is Leapfrog’s engine, FastRBF™.  ARANZ Geo founder, Rick Fright describes it as a ‘blend of expertise’ and a ‘combination of experts all at the top of their game’, many in between working at University College London or Cambridge University. Fundamentally the common theme was that they were Kiwi’s, many friends from the University of Canterbury in New Zealand.

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Gaining acceptance

This is the fifth history blog in a six part series. If you missed part four, Leapfrog’s Fast RBF™, you can find it here.

In 2004, following successful testing and use of the initial product by SRK Consulting, ARANZ Geo was formed to begin the marketing and further development of the product to the mining industry. Leapfrog Mining was born.

Too fast!

But in the early days Leapfrog® struggled to be accepted. Says Rick Fright, “People didn’t take it seriously because it was just too fast!  And it was too isotropic, it didn’t take into account folding strata.”

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Leapfrog’s Fast RBF™

This is the fourth history blog in a six part series – Leapfrog’s fast RBF. If you missed part three, Modelling in full 3D, you can find it here.

In 1999 work began on new surfacing algorithms so that an RBF implicit model could be utilised by conventional computer graphics packages. This meant converting an implicit RBF model into meshes of triangles and piecewise continuous spline surfaces.

The main difference between traditional RBF’s and what became ARANZ’s FastRBF™ is the ability to deal with large datasets of well over 1,000,000 points on ordinary computing hardware incredibly quickly. The maths used to speed up the calculation was initially used in particle physics. Filtering and approximation methods make Fast RBF™ ideal for visualising and processing non-uniformly sampled noisy data. FastRBF™ has extraordinary extrapolation capabilities, even when large gaps occur in a data set.

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Modelling in full 3D

This is the third history blog in a six part series – Modelling in full 3D. If you missed part two, Medicine, movies and outer space!, you can find it here.

In 1996 in pursuit of more mathematically robust meshes ARANZ rekindled their close collaboration with mathematician Rick Beatson. This motivated the extension of his fast RBF methods to modelling full 3D data and a new way of describing the surfaces of objects implicitly using a ‘signed-distance’ function.

Says ARANZ Geo founder Rick Fright, “Having got the scanner working, and gathered scattered point measurements from the surface of a 3D object, we realised we had an even bigger problem of reconstructing a complete and continuous surface model. So we got back in touch with Rick Beatson.”

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