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Scan registration methods can often suffer from convergence and accuracy issues when the scan points are sparse or the environment violates the assumptions the methods are founded on. We propose an alternative approach to 3D scan registration using the curve let transform that performs multi-resolution geometric analysis to obtain a set of coefficients indexed by scale (coarsest to finest), angle...
The normal distributions transform (NDT) scan registration algorithm has been shown to produce good results, however, has a tendency to converge to a local minimum if the initial parameter error is large. In order to improve the convergence basin for NDT, a multi-scale k-means NDT (MSKM-NDT) variant is proposed. This approach divides the point cloud using k-means clustering and performs the optimization...
A biologically-inspired algorithm called “Spiral Bacterial Foraging Optimization” is presented in this article in order to find the global optimum of multi-modal objective functions. The proposed algorithm is simply a multi-agent, gradient-based algorithm, such as steepest descent, which minimizes both the main objective function (local search) and the distance between each agent and a temporary central...
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