Development of IoT-Based Hybrid Autonomous Networked Robots

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.

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Publication Details

Journal
Technologies
Published
2025-04-23
DOI
https://doi.org/10.3390/technologies13050168
Citations
2
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
2.43
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article

Development of IoT-Based Hybrid Autonomous Networked Robots

Maki K. Habib, Chimsom I. Chukwuemeka
2 citations
Technologies
Robotics and Automated Systems
2.43
article

Development of IoT-Based Hybrid Autonomous Networked Robots

Maki K. Habib, Chimsom I. Chukwuemeka
article en
2 citations

Abstract

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.

TechnologiesVol. 13(5)
American University in Cairo (EG)
Openalex Percentile: Top 12%
Robotics and Automated Systems
2.43
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