This paper focuses on active sensing of nonholonomic wheeled mobile robots (WMRs). Active sensing solves the following problem: given a current knowledge about the robot state and the environment, how to select the next sensing action or sequence of actions. A vehicle is moving autonomously through a static environment gathering information from sensors. The sensor data are used to generate the robot actions in order to move around a reference trajectory with preset initial starting and desired goal configurations and imposed constraints. The paper presents a method for the determination of optimal trajectories based on optimization techniques. A suitable performance criterion is formulated to characterize the uncertainty and the extraction of information from sensor data. Finally results from experiments are given.