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mecca.louisville.edu
In robotic navigation, path planning is aimed at getting the optimum collision-free
path between a starting and target locations. The optimality criterion depends on
the surrounding environment and the running conditions. In this paper, we propose
a general, robust, and fast path planning framework for robotic navigation using
level set methods. A level set speed function is proposed such that the minimum cost
path between the starting and target locations in the environment, is the optimum
planned path. The speed function is controlled by one parameter, which takes one
of three possible values to generate either the safest, the shortest, or the hybrid
planned path. The hybrid path is much safer than the shortest path, but less shorter
than the safest one. The main idea of the proposed technique is to propagate a
monotonic wave front with a particular speed function from a starting location
until the target is reached and then extracts the optimum planned path between
them by solving an ordinary differential equation (ODE) using an effient numerical
scheme. The framework supports both local and global planning for for both 2D
and 3D environments. The robustness of the proposed framework is demonstrated
by correctly extracting planned paths of complex maps.
M. Sabry Hassouna
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Keywords fast marching methods | level set methods | optimum path | path planning | robotic navigation | skeletonization | | |||||||||
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