Abstract
Swarm robots are employed to measure scalar field on many missions. Estimating the scalar value of points near the swarm robots are necessary, when robots are deployed to explore a 2D(Two-Dimensional) scalar field or track some extreme points in it. But it would not to be effortless to get accurate value, since the sampled data are always contaminated by noise. In this paper a discrete state transition model of 2D scalar field is addressed, and this model can be implemented with the Kalman Filter for data fusion on a 2D scalar field exploration mission. The differential equation of the state vector in 2D scalar field is different from the common state transition model utilized by researchers, because the differential variable of it is not only one, however there are two different differential variables, i.e., x and y. This is also the reason why the common state transition model could not be implemented under this context. In this study, the state transition model is developed based on polar coordinate system by making assumptions about the correlation property of elements in Hessian matrix. The computer simulation is executed to prove the validity of this model when it is applied together with Kalman Filter on a 2D scalar field exploration mission performed by four robots.
Published Version
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