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Autonomous Networked Robot (ANR) systems feature multi-robot systems (MRSs) and wireless sensor networks (WSNs). These systems help to extend coverage, maximize efficiency in data routing, and provide practical and reliable task management, among others. This article presents the development and implementation of an IoT-based hybrid ANR system integrated with different cloud platforms. The system comprises two main components: the physical hybrid ANR, the simulation development environment (SDE) with hardware in the loop (HIL), and the necessary core interfaces. Both are integrated to facilitate system component development, simulation, testing, monitoring, and validation. The operational environment (local and/or distributed) of the designed system is divided into zones, and each zone comprises static IoT-based sensor nodes (SSNs) and a mobile robot with integrated onboard IoT-based sensor nodes (O-SSNs) called the mobile robot sensor node (MRSN). Global MRSNs (G-MRSNs) navigate spaces not covered by a zone. The mobile robots navigate within/around their designated spaces and to any of their SSNs. The SSNs and the O-SSN of each zone are supported by the ZigBee protocol, forming a WSN. The MRSNs and G-MRSNs communicate their collected data from different zones to the base station (BS) through the IoT base station gateway (IoT-BSG) using wireless serial protocol. The base station analyzes and visualizes the received data through GUIs and communicates data through the IoT/cloud using the Wi-Fi protocol. The developed system is demonstrated for event detection and surveillance. Experimental results of the implemented/simulated ANR system and HIL experiments validate the performance of the developed IoT-based hybrid architecture.
Details
Network topologies;
Hardware-in-the-loop simulation;
Communication;
Wireless sensor networks;
Nodes;
Robots;
Unmanned aerial vehicles;
Robot sensors;
Automation;
Localization;
Energy consumption;
Data collection;
Robotics;
Simulation;
Partial differential equations;
Artificial intelligence;
Digital twins;
Sensors;
Distributed control systems;
Underwater pipelines;
Algorithms;
Environmental monitoring;
Surveillance;
Multiple robots
; Chukwuemeka, Chimsom I 2 1 Robotics, Control and Smart Systems (RCSS), School of Sciences and Engineering, American University in Cairo (AUC), New Campus, New Cairo 11835, Egypt, Mechanical Engineering Department, University in Cairo (AUC), New Campus, New Cairo 11835, Egypt
2 Robotics, Control and Smart Systems (RCSS), School of Sciences and Engineering, American University in Cairo (AUC), New Campus, New Cairo 11835, Egypt