Annotation

Annotation: One of the design options for a mobile robot's navigation system is to use a free-of-charge navigation system (BINS) with a Zero-velocity Update (ZUPT) mechanism. This approach can provide good navigation accuracy for a mobile robot with highly noisy measurements. In pedestrian navigation methods, the BINS has no connection with the control system (CS) of the navigation object, which makes it difficult to apply the ZUPT correction method. In robots, the CS is present, so the BEANS can receive explicit information about the dynamic state of the object, which greatly increases the probability of correctly determining the resting phase. The proposed BINS algorithm is based on three basic principles: the mathematical model of the robot as a dynamic system is based on the laws of classical mechanics of Newton; the use of the Extended Kalman Filter (EKF) for data aggregation and assessment of the state of the system.; the application of the ZUPT navigation data correction method to reduce the error in determining the coordinates and orientation of the object. Performing ZUPT correction involves solving the problems of detecting the moment of stopping (zero speed) of the robot and directly correcting the parameters of the robot's condition. To detect zero speed, it is proposed to use a stop signal from the CS of robot. After reliably determining the moment of stopping, the robot's state vector is corrected and the covariance matrix of the state is adjusted. The paper presents an algorithm for the functioning of the BINS of a mobile robot and a functional scheme of the BINS. To test the operability of the mobile robot's BINS algorithm, the robot's BINS measuring module (MM) has been developed, which includes sensors of a low accuracy class. The results of experimental studies of the synthesized BINS operation algorithm conducted using the developed measuring module for the movement and navigation of a mobile robot along different trajectories are presented. In the course of experimental research, it was found that the developed algorithm, when using measurements from the one developed by the developed measuring module, allows determining the location of the robot with an error not exceeding 5% of the length of the traveled path.