Nonlinear autoregressive neural network with exogenous inputs based solution for local minimum problem of agent tracking using quadrotor
Abstract
Nonlinear autoregressive neural network with exogenous inputs based solution for local minimum problem of agent tracking using quadrotor
Incoming article date: 28.04.2014This paper offers an improvement for machine vision based tracking algorithm using NARX neural network. This is achieved by predicting the next position of a mobile agent based on previous movement described by time-series functions. The algorithm remains passive and does not interfere with the quadrotr flight path until detection of multiple agent-candidates, when the tracking algorithm is not able to identify or locate the assigned agent. Meanwhile the NARX training set are updated in parallel with each successful tracking cycle. This process is done to eliminate the overfitting problem of BPTT training.
Keywords: NARX, quadrotor, agent tracking, local minimum problem, machine vision