In this paper, we show the results of applying stochastic sampling methods such as Cross Entropy method and Sampling Based Differential Dynamic Programming method to path planning of Unmanned Ground Vehicles (UGV) on unstructured 3D terrains. We show the superiority of sampling algorithms to local optimization methods such as Gauss Newton optimization method through simulations.A high fidelity ...

To this day, most generative discussions of wh-constructions assume that Superiority Effects (SEs) are the norm, to be explained by principles of UG, and that SUVs are a secondary phenomenon, to be analyzed via D-Linking, or some other mechanism peripheral to the central concerns of grammatical theory. In the alternative approach to SUVs considered here, examples like (1b) and (2) are all treat...

A method named simple2complex for modeling and training deep neural networks is proposed. Simple2complex train deep neural networks by smoothly adding more and more layers to the shallow networks, as the learning procedure going on, the network is just like growing. Compared with learning by end2end, simple2complex is with less possibility trapping into local minimal, namely, owning ability for...

In this paper, a handwritten character recognition experiment using a monotonic and continuous twodimensional warping algorithm is reported. This warping algorithm is based on dynamic programming and searches for the optimal pixel-to-pixel mapping between given two images subject to two-dimensional monotonicity and continuity constraints. Experimental comparisons with rigid matching and local p...