Abstract
Path planning may be viewed as an optimal control problem which can be addressed using dynamic programming. The optimal control (i.e. path) is obtained after solving Bellman's dynamic programming equation for an "optimal return fuction". This paper proposes solving the Bellman equation using distributed computing paradigms which are, effectively, hardware implementations of the Bellman equation's variational solution. The approach promises to be globally optimal, fast, and easily implemented on existing parallel computing machines.
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