Neural network-based optimisation of smart odometry classification in a self-governing robot for precise position and location estimation
by Shaik Mohammad Rafi; A. Prakash; Firdouse Banu; P. Muthu Krishnammal; K. Bhavana Raj; J.E. Anusha Linda Kostka
International Journal of Engineering Systems Modelling and Simulation (IJESMS), Vol. 15, No. 5, 2024

Abstract: The Verdino self-governing robot's intelligent dummy device will benefit greatly from this study's findings. An odometric mathematical model based on the robot's trajectory equations determines the robot's position. Odometer devices are system inputs, and a model is constructed using the wheel diameter and distance. This model determines the optimal nominal parameters by trying to conduct a restricted squares reduction. This model is computed using the current wheel diameter to assure the accuracy of the findings. A neural network model is used to train an odometric model using data. There is no doubt that the neural network works.

Online publication date: Tue, 03-Sep-2024

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