## 1 Introduction
### Modern Platforms for Robotics Positioning and Communications  
Localization or positioning was considered in reviews [35; 36] as a process to obtain tracked objects information concerning multiple reference points within a predetermined area, i.e., it is a procedure to identify the position of mobile/fixed devices, including smartphones, drones, watch, beacons, and vehicles using some fixed nodes and mobile computing devices. Global navigation satellite system (GNSS) in such tasks can use signals produced by global positioning system (GPS), global navigation satellite system (GLONASS), Galileo and Beidou. As the GPS device loses substantial power in an indoor setting due to signal attenuation, such systems cannot be used for indoor localization of devices. Alternative possibilities refer to ZigBee, Bluetooth, Radio Frequency Identification (RFID), cellular networks (including LTE and 5G), ultrawideband (UWB), frequency modulation (FM), inertial sensors and Wi-Fi. Some hybrid approaches are also possible. Most common techniques for localization include time-of-flight (TOF) measurements and received signal strength indicator (RSSI) signal measurements, utilizing the distance between known fixed stations and the target device, or fingerprint-based location estimation. Vehicular ad-hoc network (VANET) [37] was based on the link-layer communication (IEEE 802.11p) and has included the data exchange between the high-speed vehicles in the licensed band of 5.9 GHz (5.850-5.925 GHz). VANET differs from other ad-hoc networks by high mobility, dynamic topology, frequent data exchange, unbounded network size, unlimited battery power, and predictable movement (which happens only on the road). It may use two types of nodes: (1) mobile nodes attached to onboard units, and (2) static nodes like traffic lamp posts, signboards, and roadside units. This network of mobile agents has provided connections vehicle-to-vehicle, vehicle-to-infrastructure, and infrastructure-to  
Figure 1: Communication network includes usual stationary nodes and autonomous mobile robotic agents 0, 1,..., which are the participants of a multi-agent system (MAS) and can follow some given route like agent 1. Nodes called checkpoints are to approve identity of the mobile agent and to give access to a requested service. Such nodes optionally may be participants of the trusted local network. infrastructure. Used performance metrics were hop length, minimum energy, link lifetime, route breakage, and bandwidth. Very actively investigated field of autonomous robotics refers to flying unmanned aerial systems (UAVs). The authors of the review [38] have analyzed flying ad-hoc networks (FANETs), which can be deployed either individually or may be incorporated into traditional wireless local area networks (WLANs). Its main application fields include search and rescue, mailing and delivery, traffic monitoring, precision agriculture, and surveillance applications. Unmanned service of FANETs is actual in case of natural disasters, hazardous gas intrusions, wildfires, avalanches, and search of missing persons. As routing is the most challenging job in FANETs due to such attributes of UAVs, as high mobility, 3D movement, and rapid topology changes, then a predictive method should be used for path planning and navigation in order to prevent possible collisions and to ensure the safety of the FANET. However, the data aggregated by a small UAV can be too large to be processed and stored onboard [39]. Small UAVs in FANETs also suffer from security vulnerabilities, as their limited storage and computing capabilities do not allow to perform computational-intensive tasks locally [40; 41]. An intruder intending to attack the network UAV [38] can transmit massive reservation requests, eavesdrop instructions, and modify the information. UAVs connected to Wi-Fi are considered as less secured in comparison with cellular networks, due to unreliable links and poor security methods.