Zbigniew Kulesza

Various unmanned aerial vechicle (UAV) applications, especially those based on reconnaissance and observation missions, often require an unlimited time of flight. This is possible only when a UAV is continuously supplied with power from a ground-based power source, which is why tethered UAV systems were developed. Tethered UAV systems are based on multicopters, which can hover above a landing pad or track its position if it is movable. The presented research concerned the development of a large C3 class hexacopter with a maximal payload of about 1 kg and a takeoff mass of 16 kg, which was tested in maritime conditions during a ferry’s cruise. The main purpose of the hexacopter was to continuously observe the area ahead of the vessel to detect and localize obstacles in the water. During the experimental tests, critical phases of flight were identified, the AC/DC power supply unit and power cord unwinder were tested, and the power required by six brushless direct current (BLDC) motors was registered. The obtained results could be useful in future work on tethered UAV systems applied in windy maritime conditions.

Various UAV applications, especially those based on reconnaissance and observation missions, often require an unlimited time of flight. This is possible only when a UAV is being continuously power supplied from the ground power source, and that is why tethered UAV systems were developed. Tethered UAV systems are based on multicopters which can hover above the landing pad, or track its position in the case it is movable. The presented research is about the development of a large C3 class hexacopter having a maximal payload of about 1 kg, and takeoff mass of 16 kg, which was tested in maritime conditions during the ferry’s cruise. The main purpose of the hexacopter is the continuous observation of the area ahead of a vessel to detect and localize obstacles in the water. During experimental tests critical phases of flight were identified, the AC-DC power supply unit as well as the power cord unwinder were tested, and the power taken by six BLDC motors was registered. The obtained results can be useful in future work on tethered UAV systems used in windy maritime conditions.

Mass casualty incident (MCI) is an unpredictable situation where a great number of people have been injured after an accident or sudden disease. Survival of the injured in the MCI depends on the efficiency of the directed emergency system (DES). The organization and management of medical assistance is of paramount importance. The shortest possible time to provide medical services to injured persons is crucial. The medical service in the case of the MCI primarily requires decisions on the priority of the order of treatment of the injured, the choice of medical transport and the location of specialized emergency treatment. As part of this paper, the effectiveness of the DES has been analyzed, and criteria used to improve rescue operations have been formulated. A formalized mathematical description of the medical rescue operations in MCIs has been proposed, and the optimization problem as the mixed integer linear programming (MILP) task was formulated. Optimization of an example case of rescue operations in MCIs has been presented. A computer simulator for optimal decision-making in medical rescue operations (CSMRO) has been developed for this purpose. The CSMRO implements various multi-criteria optimization methods to solve the formulated problem of rescue operations optimization. The results of computations made with the developed CSMRO simulator significantly shorten the time of decision-making in mass casualty incident handling.

During the design of a wheeled mobile robot, the problem of the proper selection of the parameters of its motor controllers was encountered. Knowing the parameters of the robot’s Permanent Magnet Direct Current (PMDC) motors, precise tuning of the controllers can be performed, which then results in improved robot dynamics. Among many methods of parametric model identification, optimization-based techniques, particularly genetic algorithms, have gained more and more interest recently. The articles on this topic present the results of parameter identification, but they do not refer to the search ranges for individual parameters. With too wide a range, genetic algorithms do not find solutions or are time-inefficient. This article introduces a method for determining the parameters of a PMDC motor. The proposed method performs an initial estimation of the range of searched parameters to shorten the estimation time of the bioinspired optimization algorithm.

Nowadays, most robotic systems perform their tasks in an environment that is generally known. Thus, robot's trajectory can be planned in advance depending on a given task. However, as a part of modern manufacturing systems which are faced with the requirements to produce high product variety, mobile robots should be flexible to adapt to changing and diverse environments and needs. In such scenarios, a modification of the task or a change in the environment, forces the operator to modify robot's trajectory. Such modification is usually expensive and time-consuming, as experienced engineers must be involved to program robot's movements. The current paper presents a solution to this problem by simplifying the process of teaching the robot a new trajectory. The proposed method generates a trajectory based on an initial raw demonstration of its shape. The new trajectory is generated in such a way that the errors between the actual and target end positions and orientations of the robot are minimized. To minimize those errors, the grey wolf optimization (GWO) algorithm is applied. The proposed approach is demonstrated for a two-wheeled mobile robot. Simulation and experimental results confirm high accuracy of generated trajectories.

Vibration monitoring provides a good-quality source of information about the health condition of machines, and it is often based on the use of accelerometers. This article focuses on the use of accelerometer sensors in fabricating a low-cost system for monitoring vibrations in agricultural machines, such as rotary tedders. The aim of the study is to provide useful data on equipment health for improving the durability of such machinery. The electronic prototype, based on the low-cost AVR microcontroller ATmega128 with 10-bit ADC performing a 12-bit measurement, is able to acquire data from an accelerometer weighing up to 10 g. Three sensors were exposed to low accelerations with the use of an exciter, and their static characteristics were presented. Standard experimental tests were used to evaluate the constructed machine monitoring system. The self-contained prototype system was calibrated in a laboratory test rig, and sinusoidal and multisinusoidal excitations were used. Measurements in time and frequency domains were carried out. The amplitude characteristic of the preformed system differed by no more than 15% within a frequency range of 10 Hz–10 kHz, compared to the AVM4000 commercial product. Finally, the system was experimentally tested to measure acceleration at three characteristic points in a rotational tedder, i.e., the solid grease gearbox, the drive shaft bearing and the main frame. The RMS amplitude values of the shaft vibrations on the bearing in relation to the change in the drive shaft speed of two tedders of the same type were evaluated and compared. Additionally, the parameters of kurtosis and crest factor were compared to ascertain the bearing condition.