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Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs

Real-time flight controllers are becoming dependent on general-purpose operating systems, as the modularity and complexity of guidance, navigation, and control systems and algorithms increases. The non-deterministic nature of operating systems creates a critical weakness in the development of motion...

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Autores principales: Silva Cotta, Joao Leonardo, Agar, Daniel, Bertaska, Ivan R., Inness, John P., Gutierrez, Hector
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10674650/
https://www.ncbi.nlm.nih.gov/pubmed/38005655
http://dx.doi.org/10.3390/s23229269
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author Silva Cotta, Joao Leonardo
Agar, Daniel
Bertaska, Ivan R.
Inness, John P.
Gutierrez, Hector
author_facet Silva Cotta, Joao Leonardo
Agar, Daniel
Bertaska, Ivan R.
Inness, John P.
Gutierrez, Hector
author_sort Silva Cotta, Joao Leonardo
collection PubMed
description Real-time flight controllers are becoming dependent on general-purpose operating systems, as the modularity and complexity of guidance, navigation, and control systems and algorithms increases. The non-deterministic nature of operating systems creates a critical weakness in the development of motion control systems for robotic platforms due to the random delays introduced by operating systems and communication networks. The high-speed operation and sensitive dynamics of UAVs demand fast and near-deterministic communication between the sensors, companion computer, and flight control unit (FCU) in order to achieve the required performance. In this paper, we present a method to assess communications latency between a companion computer and an RTOS open-source flight controller, which is based on an XRCE-DDS bridge between clients hosted in the low-resource environment and the DDS network used by ROS2. A comparison based on the measured statistics of latency illustrates the advantages of XRCE-DDS compared to the standard communication method based on MAVROS-MAVLink. More importantly, an algorithm to estimate latency offset and clock skew based on an exponential moving average filter is presented, providing a tool for latency estimation and correction that can be used by developers to improve synchronization of processes that rely on timely communication between the FCU and companion computer, such as synchronization of lower-level sensor data at the higher-level layer. This addresses the challenges introduced in GNC applications by the non-deterministic nature of general-purpose operating systems and the inherent limitations of standard flight controller hardware.
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spelling pubmed-106746502023-11-18 Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs Silva Cotta, Joao Leonardo Agar, Daniel Bertaska, Ivan R. Inness, John P. Gutierrez, Hector Sensors (Basel) Article Real-time flight controllers are becoming dependent on general-purpose operating systems, as the modularity and complexity of guidance, navigation, and control systems and algorithms increases. The non-deterministic nature of operating systems creates a critical weakness in the development of motion control systems for robotic platforms due to the random delays introduced by operating systems and communication networks. The high-speed operation and sensitive dynamics of UAVs demand fast and near-deterministic communication between the sensors, companion computer, and flight control unit (FCU) in order to achieve the required performance. In this paper, we present a method to assess communications latency between a companion computer and an RTOS open-source flight controller, which is based on an XRCE-DDS bridge between clients hosted in the low-resource environment and the DDS network used by ROS2. A comparison based on the measured statistics of latency illustrates the advantages of XRCE-DDS compared to the standard communication method based on MAVROS-MAVLink. More importantly, an algorithm to estimate latency offset and clock skew based on an exponential moving average filter is presented, providing a tool for latency estimation and correction that can be used by developers to improve synchronization of processes that rely on timely communication between the FCU and companion computer, such as synchronization of lower-level sensor data at the higher-level layer. This addresses the challenges introduced in GNC applications by the non-deterministic nature of general-purpose operating systems and the inherent limitations of standard flight controller hardware. MDPI 2023-11-18 /pmc/articles/PMC10674650/ /pubmed/38005655 http://dx.doi.org/10.3390/s23229269 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Silva Cotta, Joao Leonardo
Agar, Daniel
Bertaska, Ivan R.
Inness, John P.
Gutierrez, Hector
Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs
title Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs
title_full Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs
title_fullStr Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs
title_full_unstemmed Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs
title_short Latency Reduction and Packet Synchronization in Low-Resource Devices Connected by DDS Networks in Autonomous UAVs
title_sort latency reduction and packet synchronization in low-resource devices connected by dds networks in autonomous uavs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10674650/
https://www.ncbi.nlm.nih.gov/pubmed/38005655
http://dx.doi.org/10.3390/s23229269
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