Research on Trajectory Prediction of Tracked Vehicles Based on Real Time Slip Estimation

In order to realize the unmanned driving of tracked vehicle, its future motion trajectory within a period of time should be accurately predicted in trajectory planning. It is difficult to predict the future motion trajectory of vehicle due to the slippage between tracks and ground. A kinematics model based on the instantaneous steering center is developed by studying the interaction of track and ground. The relative pose of vehicle is a function of the slippage parameters, and the Jacobi matrix is difficult to solve. For this problem, the analytical solutions of Jacobi matrix are deduced by linearizoffing the functional differential equations. Slippage parameters are solved iteratively using Levenberg-Marquardt method according to the calculated and measured pose errors, and a set of input commands is given to predict the future motion trajectory within a period of time. The proposed method is used to update the slip parameters in real time without prior knowledge of terrain parameters. The real vehicle tests show that the position errors predicted using this method are reduced by more than 30% compared to the traditional trajectory prediction method.