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paper covers the problem of Collision Free Path Planning for an autonomous robot and proposes a solution to it through the Back Propagation Neural Network. The solution is transformed into a composition of matrix-multiplication operations, which is a classic example of problems that can be efficiently parallelized. This paper finally proposes a parallel implementation of this matrix-multiplication method which, in itself, encapsulates the neural network that implements the collision free path planning for an autonomous robot.

A Parallelized Matrix-Multiplication Implementation of Neural Network for Collision Free Robot Path Planning