A modular reconfigurable robot (MRR) is considered as a system of systems; that is, a robot control system consists of modular systems. For an MRR, onboard tracking of multiple objects is one of the most challenging tasks. This is because the task requires lots of computation resources, but an MRR system is constrained by several physical limitations. To enhance the computing performance of an MRR control system, a novel approach to organizing a distributed computing system is proposed. The key components of the proposed approach are FPGA-based specialized computational cores (SCCs). An SCC for tracking objects is designed to utilize spare resources of the MRR module's control devices. Analysis and experiments on a real testbench are performed to illustrate that the proposed approach can enhance overall computing performance of an MRR control system without adding additional components. As such, weight and dimensional parameters are saved; unnecessary power consumption and heat generation are reduced. One experimental example shows that the proposed SCC enables a Kalman filter to track objects up to 100 times faster than a comparable solution implemented with microcontrollers, while the whole distributed computing system can outperform a similar one built on high-performance CPUs.

The article is devoted to the comparison of different hardware implementations of field-oriented control (FOC) for asynchronous motor controller in terms of the control quality, the required amount of FPGA resources and the maximum synthesis frequency. FOC controllers, based on the Kalman filter and the Luenberger filter were considered. This controllers were implemented with ordinary operations of the pulse-code modulated signals and with pulse mathematical operations on the sigma-delta modulated signal, and with combinations of these methods. The conclusion was made about the applying of each regulator.

Objectives. Sports events are currently among the most promising areas for the application of tracking systems. In most cases, such systems are designed to track moving objects in a two-dimensional plane, e.g., players on the field, as well as to identify them by various features. However, as new sports such as drone racing are developed, the problem of determining the position of an object in a three-dimensional coordinate system becomes relevant. The aim of the present work was to develop algorithms and software for a method to perform 3D tracking of moving objects, regardless of the data segmentation technique, and to test this method to estimate the tracking quality.Methods. A method for matching information on the speed and position of objects was selected based on a review and analysis of contemporary tracking methods.Results. The structure of a set of algorithms comprising software for a moving-object tracker for sports events is proposed. Experimental studies were performed on the publicly available APIDIS dataset, where a MOTA metric of 0.858 was obtained. The flight of an FPV quadcopter along a track was also tracked according to the proposed dataset; the 3D path of the drone flight was reconstructed using the tracker data.Conclusions. The results of the experimental studies, which demonstrated the feasibility of using the proposed method to track a quadcopter flight trajectory in a three-dimensional world coordinate system, is also showed that the method is suitable for tracking objects at sports events.

The paper discusses the composition and requirements for sensors in the group of surveillance robots. Classification and quality criteria for sensor data processing algorithms for the surveillance robotics are proposed. From the point of view of the criteria, the sensor data processing methods are performed. The structure of the surveillance robots control system software is proposed.

The paper discusses the task of detecting and determining the spatial position of moving objects according to their dynamic characteristics and with using the aggregation of the sensors of robotic systems. A model of a generalized sensor and classifier according to its indications is proposed. An algorithm for the results of classification processing and determining the spatial position of objects is developed.