Automatic Multivector Differentiation and Optimization
Journal article, Peer reviewed
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Original versionAdvances in Applied Clifford Algebras 2016 10.1007/s00006-016-0722-6
In this work, we present a novel approach to non-linear optimization of multivectors in the Euclidean and conformal model of geometric algebra by introducing automatic differentiation. This is used to compute gradients and Jacobian matrices of multivector valued functions for use in non-linear optimization where the emphasis is on the estimation of rigid body motions.