Neural network based systems have been used in past years for robot navigation applications becau... more Neural network based systems have been used in past years for robot navigation applications because of their ability to learn human expertise and to utilize this knowledge to develop autonomous navigation strategies. In this paper, neural based systems are developed for mobile robot reactive navigation. The proposed systems transform sensors' input to yield wheel velocities. Novel algorithm is proposed for optimal training of neural network. With a view to ascertain the efficacy of proposed system; developed neural system's performance is compared to other neural and fuzzy based approaches. Simulation results show effectiveness of proposed system in all kind of obstacle environments.
Neural network based systems have been used in past years for robot navigation applications becau... more Neural network based systems have been used in past years for robot navigation applications because of their ability to learn human expertise and to utilize this knowledge to develop autonomous navigation strategies. In this paper, neural based systems are developed for mobile robot reactive navigation. The proposed systems transform sensors' input to yield wheel velocities. Novel algorithm is proposed for optimal training of neural network. With a view to ascertain the efficacy of proposed system; developed neural system's performance is compared to other neural and fuzzy based approaches. Simulation results show effectiveness of proposed system in all kind of obstacle environments.
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Papers by Masood Ahmed