Target tracking by grey prediction theory and look-ahead fuzzy logic control

Target tracking is useful in many robotics applications, such as assembly, autonomous navigation, etc. Conventional position based tracking strategies usually define the dynamics models for either motion control on tracker or position prediction on target, making the system inflexible and difficult to implement. This paper presents a new target tracking strategy, in which the dynamics model parameters are online updated according to the limited observation of the target and tracker relation. The grey theory is used in the position prediction of the target, which predicts the future trend based on the previous sensory measurements. We also use the look-ahead fuzzy logic for motion control of the tracker. Experimental results for tracking different moving targets are accomplished by the “Chung Cheng-1” mobile robot used in our laboratory. The results demonstrate the robustness and flexibility of the system