Aerial Robot Coworkers for Autonomous Localization of Missing Tools in Manufacturing Plants

Dios, J.R. Martínez-de; Torres-González, Arturo; Paneque, J.L.; Fuego-Garcia, Dimas; Ramírez, Juan Ramón Astorga; Ollero, A.

doi:10.1109/icuas.2018.8453291

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…Nodes, R and BS are equipped with Ultra Wide Band (UWB) devices. R localizes the nodes and BS integrating UWB measurements using Particle Filters [64], which provided sufficiently low localization error indoors and outdoors. SNSR was configured with SEC_LTE.…”

Section: B Performance Evaluation and Validationmentioning

confidence: 99%

A Robot–Sensor Network Security Architecture for Monitoring Applications

Fernández-Jiménez¹,

Dios

2022

IEEE Internet Things J.

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This paper presents SNSR (Sensor Network Security using Robots), a novel, open, and flexible architecture that improves security in static sensor networks by benefiting from robot-sensor network cooperation. In SNSR, the robot performs sensor node authentication and radio-based localization (enabling centralized topology computation and route establishment) and directly interacts with nodes to send them configurations or receive status and anomaly reports without intermediaries. SNSR operation is divided into stages set in a feedback iterative structure, which enables repeating the execution of stages to adapt to changes, respond to attacks, or detect and correct errors. By exploiting the robot capabilities, SNSR provides high security levels and adaptability without requiring complex mechanisms. This paper presents SNSR, analyzes its security against common attacks, and experimentally validates its performance.

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Section: B Performance Evaluation and Validationmentioning

confidence: 99%

A Robot–Sensor Network Security Architecture for Monitoring Applications

Fernández-Jiménez¹,

Dios

2022

IEEE Internet Things J.

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“…• AGVs and drones [36,67] play a major role in moving objects within a distribution center. The objects may be parcels [68], pallets [69], or even tools to assist the workers [70]. These vehicles may also be used for other purposes such as surveillance [71].…”

Section: Industry 40 Applications In Logisticsmentioning

confidence: 99%

Optimization of 5G Networks for Smart Logistics

Khatib

Barco

2021

Energies

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Industry 4.0 is generalizing the use of wireless connectivity in manufacturing and logistics. Specifically, in Smart Logistics, novel Industry 4.0 technologies are used to enable agile supply chains, with reduced management, energy and storage costs. Cellular networks allow connectivity throughout all the scenarios where logistics processes take place, each having their own challenges. This paper explores such scenarios and challenges, and proposes 5G technology as a global unified connectivity solution. Moreover, this paper proposes a system for exploiting the application-specific optimization capabilities of 5G networks to better cater for the needs of Smart Logistics. An application traffic modeling process is proposed, along with a proactive approach to network optimization that can improve the Quality of Service and reduce connectivity costs.

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“…Robot localization is a traditional problem in robotics where many successful techniques have been developed [2], [10]- [12]. The need for robots autonomously navigating in more and more complex environments [13] has motivated intense R&D efforts in multi-sensor pose estimation. Very good methods have been developed fusing camera or LIDAR with IMU, altimeter, and many other sensors [6], [14], [15].…”

Section: Related Workmentioning

confidence: 99%

Multi-Sensor 6-DoF Localization For Aerial Robots In Complex GNSS-Denied Environments

Paneque

Dios

Ollero

2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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The need for robots autonomously navigating in more and more complex environments has motivated intense R&D efforts in making robot pose estimation more accurate and reliable. This paper presents a multi-sensor multi-hypothesis method for robust 6-DoF localization in complex environments. Robustness and accuracy requirements are addressed as follows. First, camera and LIDAR features are seamlessly integrated in the same statistical framework, benefiting from their synergies and providing robustness in scenarios with low or varying densities of LIDAR and visual features. Second, a multi-hypothesis approach is adopted to cope with scenario symmetries. The method has been carefully designed to operate in real time using feature and hypothesis filtering and efficient hypothesis refinement, and has been coded in a multi-core implementation. The proposed method has been extensively validated for closedloop aerial robot navigation in different urban and industrial scenarios and has shown advantages over well-known singlesensor techniques.

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Aerial Robot Coworkers for Autonomous Localization of Missing Tools in Manufacturing Plants

Cited by 6 publications

References 22 publications

A Robot–Sensor Network Security Architecture for Monitoring Applications

A Robot–Sensor Network Security Architecture for Monitoring Applications

Optimization of 5G Networks for Smart Logistics

Multi-Sensor 6-DoF Localization For Aerial Robots In Complex GNSS-Denied Environments

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