Distributed and Synchronized Setup towards Real-Time Robotic Control using ROS2 on Linux

Puck, L.; Keller, Philip; Schnell, T.; Plasberg, C.; Tanev, Atanas; Heppner, G.; Roennau, Arne; Dillmann, Rüdiger

doi:10.1109/case48305.2020.9217010

Cited by 13 publications

(7 citation statements)

References 3 publications

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“…To meet safety and/or performance goals, some parts of a system must execute in deterministic amounts of time. ROS 2 offers APIs for developers of realtime systems to enforce application-specific constraints [33], [34].…”

Section: B Designmentioning

confidence: 99%

Robot Operating System 2: Design, architecture, and uses in the wild

Macenski

Foote²,

Gerkey³

et al. 2022

Sci. Robot.

424

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The next chapter of the robotics revolution is well underway with the deployment of robots for a broad range of commercial use cases. Even in a myriad of applications and environments, there exists a common vocabulary of components that robots share—the need for a modular, scalable, and reliable architecture; sensing; planning; mobility; and autonomy. The Robot Operating System (ROS) was an integral part of the last chapter, demonstrably expediting robotics research with freely available components and a modular framework. However, ROS 1 was not designed with many necessary production-grade features and algorithms. ROS 2 and its related projects have been redesigned from the ground up to meet the challenges set forth by modern robotic systems in new and exploratory domains at all scales. In this Review, we highlight the philosophical and architectural changes of ROS 2 powering this new chapter in the robotics revolution. We also show through case studies the influence ROS 2 and its adoption has had on accelerating real robot systems to reliable deployment in an assortment of challenging environments.

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Section: B Designmentioning

confidence: 99%

Robot Operating System 2: Design, architecture, and uses in the wild

Macenski

Foote²,

Gerkey³

et al. 2022

Sci. Robot.

424

View full text Add to dashboard Cite

show abstract

“…The overall performance of ROS 2 is considered superior to its ROS 1 predecessor [10], [11], [12]. To assess this performance, a number of tools have been proposed to evaluate the message transmission latency.…”

Section: B Ros 2 Tracingmentioning

confidence: 99%

Analyze, Debug, Optimize: Real-Time Tracing for Perception and Mapping Systems in ROS 2

Lajoie¹,

Bédard²,

Beltrame³

2022

Preprint

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Perception and mapping systems are among the most computationally, memory, and bandwidth intensive software components in robotics. Therefore, analysis, debugging, and optimization are crucial to improve perception systems performance in real-time applications. However, standard approaches often depict a partial picture of the actual performance. Fortunately, instrumentation and tracing offer a great opportunity for detailed performance analysis of realtime systems. In this paper, we show how our novel opensource tracing tools and techniques for ROS 2 enable us to identify delays, bottlenecks and critical paths inside centralized, or distributed, perception and mapping systems.

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“…It can also be implemented in different mobile robot platforms, as ROS2 ensures the communication compatibility. In addition to the modularity, it also provides fully encrypted communication through the DDS layer of ROS2 [14]. It can also be implemented in different mobile robot platforms, as ROS2 ensures the communication compatibility.…”

Section: Approachmentioning

confidence: 99%

“…It can also be implemented in different mobile robot platforms, as ROS2 ensures the communication compatibility. In addition to the modularity, it also provides fully encrypted communication through the DDS layer of ROS2 [14]. In this way, no external influence can manipulate the information from the camera and the embedded device, which is crucial for the safety of the robot and the environment.…”

Section: Approachmentioning

confidence: 99%

“…We have developed an approach for deploying, optimizing and using open-source Detectron2 framework for machine vision tasks, together with ROS2. As a communications framework, ROS2 [14] ensures safe and secure transfer of information onboard with the robot, and wireless to a control station. The AI-Box can easily be installed onto a mobile robot to extend its capabilities.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Embedded AI-Box for Visual Detection and Inspection with Mobile Robots in ROS2

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

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Computer vision has made impressive progress in recent years due to the surge of deep learning (DL). Many DL approaches have been developed to detect, classify and segment many kinds of objects. Most of these models require a large amount of data and computing resources for training. This is specially inconvenient for mobile robots and embedded systems, because they have limited hardware and energy. We present a modular approach for a distributed system and an AI-Box for visual detection of objects and persons. The AI-Box has dedicated hardware for DL, a camera, and it runs ROS2 and Detectron2. The AI-Box can easily be installed onto a mobile robot to extend its capabilities. The trained model is optimized and reduced using pruning and quantization. Finally, the model is executed on the AI-box installed on the robot. We show how the AI-Box can be integrated onto a quadruped robot (Spot). The AI-Box can run "compressed" DL vision models and provide detection capabilities to the robot. We also show that AI-Box can also be easily extended to run different models for detection, classification and segmentation. By using a system like this, mobile robots can be enhanced with powerful models trained offline for different capabilities.

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Distributed and Synchronized Setup towards Real-Time Robotic Control using ROS2 on Linux

Cited by 13 publications

References 3 publications

Robot Operating System 2: Design, architecture, and uses in the wild

Robot Operating System 2: Design, architecture, and uses in the wild

Analyze, Debug, Optimize: Real-Time Tracing for Perception and Mapping Systems in ROS 2

Embedded AI-Box for Visual Detection and Inspection with Mobile Robots in ROS2

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