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Simple Application of Kalman Filter On a Moving Object in Unity3D

Robotic development has allowed human to be able to interact with robots. Humanoid shaped robot can make the interaction between human and robot feels more natural. One of the research of humanoid robot is to use Kinect to move the robot’s arm. Error or noise, like data jitter or random spike, often occur in Kinect data. This error can be overcome by filtering process. One of the famous filter is Kalman Filter (KF). KF is a recursive algorithm for estimating data that has a lot of noise. KF combines state model of a system and noisy measurement to get the optimal data. KF is used for linear transition function system, whereas Extended Kalman Filter (EKF) is used for system under non-linear transition function. The purpose of this paper is to show and explain the simple application of KF on moving object in Unity 3D.