\r\nfor Unmanned Aerial Vehicles (UAVs) through the application of the

\r\nRapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm.

\r\nRRT*-Smart is a sampling process of positions of a navigation

\r\nenvironment through a tree-type graph. The algorithm consists of

\r\nrandomly expanding a tree from an initial position (root node) until

\r\none of its branches reaches the final position of the path to be

\r\nplanned. The algorithm ensures the planning of the shortest path,

\r\nconsidering the number of iterations tending to infinity. When a

\r\nnew node is inserted into the tree, each neighbor node of the

\r\nnew node is connected to it, if and only if the extension of the

\r\npath between the root node and that neighbor node, with this new

\r\nconnection, is less than the current extension of the path between

\r\nthose two nodes. RRT*-smart uses an intelligent sampling strategy

\r\nto plan less extensive routes by spending a smaller number of

\r\niterations. This strategy is based on the creation of samples\/nodes

\r\nnear to the convex vertices of the navigation environment obstacles.

\r\nThe planned paths are smoothed through the application of the

\r\nmethod called quintic pythagorean hodograph curves. The smoothing

\r\nprocess converts a route into a dynamically-viable one based on the

\r\nkinematic constraints of the vehicle. This smoothing method models

\r\nthe hodograph components of a curve with polynomials that obey

\r\nthe Pythagorean Theorem. Its advantage is that the obtained structure

\r\nallows computation of the curve length in an exact way, without the

\r\nneed for quadratural techniques for the resolution of integrals.","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 137, 2018"}