Safe speed control of unmanned ground vehicle under ego-position uncertainty
The speed control system of the unmanned ground vehicle (UGV) is propose. It utilizes mathematical model of UGV, the trajectory control system and Monte-Carlo localization algorithm. The control system converts the planned trajectory into control signals, which surves as inputs for the UGV mathematical model. The output of the model is the predicted trajectory of the vehicle. Predicted trajectory is applied to each particle – hypothesis about the vehicle. pose Based on the particles trajectories prediction the collision probability is calculated and the safe speed is chosen. The proposed algorithm was tested on the real UGV. Experimental results demonstrait that the developed dynamic model allows to accurately predict the UGV trajectory and the speed control system reduces the speed to safe values while performing maneuvers and traversing narrow passages. The behavior of the system is analogous to the one of the driver reducing speed in the complex and ambiguous situations on the road.