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.
motion safety, motion safety, collision probability, risk evaluation, unmanned vehicle, dynamic model, localization of
Monte-Carlo, particle filter
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