An important addition to inertial navigation systems is the magnetometer. Areas with magnetic field anomalies serve to determine the reference points. However, magnetometers can be influenced by both the robot’s configuration and its electrical equipment. Compensation for the robot’s self-influence on the readings of the magnetometers is carried out by computer tools. In order to obtain the initial data, live experiments are required in a natural environment. To simplify data acquisition concerning the behaviour of the magnetometric systems of a mobile robot, a special facility that allows for the local compensation of the Earth’s magnetic field is used, and an artificial magnetic field that varies according to a predetermined algorithm is created. Using this facility, we can also simulate the magnetic field that will be present in the intended environment of the application of the robot. The facility features are a working space that is sufficient to place the mobile robot; a coil temperature drift correction; uniformity of the frequency response in operating frequency range; compensation for the power supply interference and similar disturbances; sensitivity equalisation of control channels; compensation for the misalignment of the sensor’s and coil system’s coordinate systems. An interactive Simulink model is designed and evaluated. The automated stand is created as an experimental facility, its parameters proving the proposed model’s adequacy.

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This article focuses on mobile robot convoying along a path travelled by a certain leader carrying the active ultrasonic beacon. The robot is equipped with the three-dimensional receiver array in order to receive both the ultrasonic wave and the RF wave marking the beginning of the measurement cycle. To increase measurement reliability, each receiver contains two independent measurement channels with automatic gain control. The distance measurements are pre-processed in order to identify the artefacts and then either remove them or replace them with the interpolated value. To estimate the position of the beacon in the robot’s local coordinate system, several methods are used, including the least squares method with subsequent exponential smoothing, the linear Kalman filter, the Rauch-Tung-Striebel smoother, the extended Kalman Filter, the unscented Kalman filter, and the particle filter. The experiments were undertaken in order to estimate the estimation method preferable for following the leader’s path.

The main goal of this research is to increase the measurement resolution of ultrasonic rangefinders to meet the needs of vital signs noncontact registration based on chest movements. The two-phase method is proposed to make distance estimates by sending probe pulse trains, calculating the phase spectrum of the echo signal’s envelope, and tracking its relevant components. During the first phase, rough Time-of-Flight (ToF)-based estimates are made. During the second phase, this estimate is corrected based on the phase spectrum of the echo signal’s envelope, the phase ambiguity is removed, and the relevant components are determined. The final estimate of the human chest displacement is calculated based on these relevant components. The output data rate is the same as for the ToF-based measurements, but the measurement resolution is increased to one hundredth of the ultrasonic wavelength. The experiment results are provided for the both model and the real human chest displacements caused by the respiration and heartbeat processes.