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We propose an algorithm to compute the dynamics of articulated rigid-bodieswith different sensor distributions. Prior to the on-line computations, theproposed algorithm performs an off-line optimisation step to simplify thecomputational complexity of the underlying solution. This optimisation stepconsists in formulating the dynamic computations as a system of linearequations. The computational complexity of computing the associated solution isreduced by performing a permuted LU-factorisation with off-line optimisedpermutations. We apply our algorithm to solve classical dynamic problems:inverse and forward dynamics. The computational complexity of the proposedsolution is compared to `gold standard' algorithms: recursive Newton-Euler andarticulated body algorithm. It is shown that our algorithm reduces the numberof floating point operations with respect to previous approaches. We alsoevaluate the numerical complexity of our algorithm by performing tests ondynamic computations for which no gold standard is available.

Inverse, forward and other dynamic computations computationally optimized with sparse matrix factorizations