Rule-based velocity selection for mobile robots under uncertainties
Zoltán Gyenes, Emese Gincsainé Szádeczky-Kardoss · 2020
The velocity selection for mobile robots, that results a collision-free motion between moving and static obstacles, is a challenging task of planning algorithms. In this paper, a novel concept is introduced that uses a grid for the investigation of the possible velocity vectors of the agent. Next to the rule-based velocity selection strategies, which can be applied both in right-hand and left-hand traffic, the uncertainties of the measured data of positions and velocity vectors of the obstacles are also considered. Using a cost function, an appropriate solution can be calculated that ensures a feasible motion for the agent. As an assumption, during a time interval the velocities of the obstacles will are unchanged. The algorithm is tested in simulation environment.