Matrix-Binary Codes based Genetic Algorithm for path planning of mobile robot

Abstract

The paper presents the new variant of genetic algorithm using the binary codes through matrix for mobile robot navigation (MRN) in static and dynamic environment. The path planning strategy is established using the trace theory as the optimum controller, Sylvester Law of Inertia (SLI) and matrix simulation. The Matrix-Binary Codes based Genetic Algorithm (MGA) transforms the environment from chaos to array. Importantly, the paper proves the SLI by the real and experimental results for the statement “any robotics randomized environment transforms into the array.” Hence the model is presented as pre-optimized robotics by SLI and post-optimized robotics by trace. The simulation result is presented by using MATLAB software and the result obtained by proposed controller is optimal with respect to path and time when compared to other intelligent navigational controller.