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Cloud-Native Fog robotics: Model-Based Deployment and Evaluation of Real-Time Applications

IEEE roboticS AND automation LETTERS 2025年第1期10卷 398-405页

作者： Wen, Long Zhang, Yu Rickert, Markus Lin, Jianjie Pan, Fengjunjie Knoll, Alois Tech Univ Munich Sch Computat Informat & Technol Robot Artificial Intelligence & Real Time Syst D-80333 Munich Germany Univ Bamberg Fac Informat Syst & Appl Comp Sci Multimodal Intelligent Interact D-96047 Bamberg Germany Mercedes Benz Grp RD ASF Driver Abstract D-70372 Stuttgart Germany

As the field of robotics evolves, robots become increasingly multi-functional and complex. Currently, there is a need for solutions that enhance flexibility and computational power without compromising real-time performance. The emergence of fog computing and cloud-native approaches addresses these challenges. In this paper, we integrate a microservice-based architecture with cloud-native fog robotics to investigate its performance in managing complex robotic systems and handling real-time tasks. Additionally, we apply model-based systems engineering (MBSE) to achieve automatic configuration of the architecture and to manage resource allocation efficiently. To demonstrate the feasibility and evaluate the performance of this architecture, we conduct comprehensive evaluations using both bare-metal and cloud setups, focusing particularly on real-time and machine-learning-based tasks. The experimental results indicate that a microservice-based cloud-native fog architecture offers a more stable computational environment compared to a bare-metal one, achieving over 20% reduction in the standard deviation for complex algorithms across both CPU and GPU. It delivers improved startup times, along with a 17% (wireless) and 23% (wired) faster average message transport time. Nonetheless, it exhibits a 37% slower execution time for simple CPU tasks and 3% for simple GPU tasks, though this impact is negligible in cloud-native environments where such tasks are typically deployed on bare-metal systems.

关键词： Robots Microservice architectures Computer architecture Robot kinematics Real-time systems Resource management software Hardware Modeling Edge computing Hardware-software integration in robotics software architecture for robotic and automation

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Active perception network for non-myopic online exploration and visual surface coverage

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INTERNATIONAL JOURNAL OF roboticS RESEARCH 2025年第2期44卷 247-272页

作者： Vutetakis, David Xiao, Jing Univ North Carolina Dept Comp Sci Charlotte NC USA Worcester Polytech Inst Dept Robot Engn Worcester MA USA

This work addresses the problem of online exploration and visual sensor coverage of unknown environments. We introduce a novel perception roadmap we refer to as the Active Perception Network (APN) that serves as a hierarchical topological graph describing how to traverse and perceive an incrementally built spatial map of the environment. The APN state is incrementally updated to expand a connected configuration space that extends throughout as much of the known space as possible, using efficient difference-awareness techniques that track the discrete changes of the spatial map to inform the updates. A frontier-guided approach is presented for efficient evaluation of information gain and covisible information, which guides view sampling and refinement to ensure maximum coverage of the unmapped space is maintained within the APN. The updated roadmap is hierarchically decomposed into subgraph regions which we use to facilitate a non-myopic global view sequence planner. A comparative analysis to several state-of-the-art approaches was conducted, showing significant performance improvements in terms of total exploration time and surface coverage, and demonstrating high computational efficiency that is scalable to large and complex environments.

关键词： Aerial systems: perception and autonomy reactive and sensor-based planning software tools for robot programming software architecture for robotic and automation

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CAD2SLAM: Adaptive Projection Between CAD Blueprints and SLAM Maps

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IEEE roboticS AND automation LETTERS 2025年第2期10卷 1529-1536页

作者： Bayon-Gutierrez, Martin Prieto-Fernandez, Natalia Garcia-Ordas, Maria Teresa Benitez-Andrades, Jose Alberto Alaiz-Moreton, Hector Grisetti, Giorgio Univ Leon Dept Elect Syst & Automatic Engn Leon 24071 Spain Univ Leon Dept Comp Control & Management Engn Antonio Rubert I-00185 Rome Italy

robotic mobile platforms are key building blocks for numerous applications and cooperation between robots and humans is a key aspect to enhance productivity and reduce labor cost. To operate safely, robots typically rely on a custom map of the environment that depends on the sensor configuration of the platform. In contrast, blueprints stand as an abstract representation of the environment. The use of both CAD and SLAM maps allows robots to collaborate using the blueprint as a common language, while also easing the control for non-robotics experts. In this work we present an adaptive system to project a 2D pose in the blueprint to the SLAM map and vice-versa. Previous work in the literature aims at morphing a SLAM map to a previously available map. In contrast, CAD2SLAM does not alter the internal map representation used by the SLAM and localization algorithms running on the robot, preserving its original properties. We believe that our system is beneficial for the control and supervision of multiple heterogeneous robotic platforms that are monitored and controlled through the CAD map. Finally, we present a set of experiments that support our claims as well as open-source implementation.

关键词： Simultaneous localization and mapping Robots Robot sensing systems Navigation Location awareness Solid modeling Accuracy Floors Collaboration Pipelines software architecture for robotic and automation computational geometry mapping computational geometry

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CNS Flight Stack for Reproducible, Customizable, and Fully Autonomous Applications

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IEEE roboticS AND automation LETTERS 2022年第4期7卷 11283-11290页

作者： Scheiber, Martin Fornasier, Alessandro Jung, Roland Bohm, Christoph Dhakate, Rohit Stewart, Christian Steinbrener, Jan Weiss, Stephan Brommer, Christian Univ Klagenfurt Inst Smart Syst Technol Grp Control Networked Syst A-9020 Klagenfurt Austria Aperture Robot LLC Santa Barbara CA 93103 USA

While low-level auto pilot stacks for aerial vehicles focus on robust control, sensing, and estimation, the continuous advancement of higher-level autonomy for aerial vehicles requires much more complex higher-level flight stacks in order to enable safe, fully autonomous long-duration missions. Rather than focusing on the low-level control, high-level flight stacks are required to monitor the system's integrity continuously, initiate contingency plans, execute mission plans and adapt them in non-nominal situations, allow for proper data logging, and provide standardized interfaces and integrity verification for external mission planners and localization modules. To that end, we present our freely available, high-level flight stack dubbed CNS Flight Stack that meets the above requirements and at the same time a) is platform-agnostic through a generalized (embedded) hardware abstraction layer, b) uses low compute complexity for online use on embedded hardware, and c) can he extended with other sensor modalities, integrity checks, and mission modules. These additional properties make it reproducible on a variety of different platforms for safe and fully autonomous applications. We tested the proposed flight stack in over 450 real-world flights and report the failure modes our framework detected and also mitigated to avoid crashes of the aerial system.

关键词： software architecture for robotic and automation autonomous vehicle navigation aerial systems: perception and autonomy

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Oops! It's Too Late. Your Autonomous Driving System Needs a Faster Middleware

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IEEE roboticS AND automation LETTERS 2021年第4期6卷 7301-7308页

作者： Wu, Tianze Wu, Baofu Wang, Sa Liu, Liangkai Liu, Shaoshan Bao, Yungang Shi, Weisong Chinese Acedemy Sci State Key Lab Comp Architecture Inst Comp Technol Beijing 100089 Peoples R China Univ Chinese Acad Sci Beijing 100089 Peoples R China Hangzhou Dianzi Univ Sch Comp Sci & Technol Hangzhou 310018 Peoples R China Wayne State Univ Detroit MI 48202 USA Univ Chinese Acad Sci State Key Lab Comp Architecture Inst Comp Technol Nanjing Peoples R China Univ Chinese Acad Sci Inst Comp Technol Nanjing Nanjing 100190 Peoples R China PerceptIn Santa Clara CA 95054 USA Univ Chinese Acad Sci State Key Lab Comp Architecture Inst Comp Technol Beijing 100190 Peoples R China Peng Cheng Lab Beijing 100190 Peoples R China

Autonomous Driving (AD) has entered a period of rapid development in recent years. With the amount of sensors and control logics installed increasing tremendously to guarantee robustness, a big challenge is posed for AD middleware. Both the academia and the industry are eager for an investigation of the performance of middlewares in Autonomous Driving Vehicles (AVs). To fill this gap, we summarize typical communication scenarios of AVs and evaluate different communication mechanisms of three popular open-source middlewares comprehensively. Besides, we construct a benchmark pack named ComP which consists of a perception communication scenario and a group of real AD applications for researchers to assess middleware performance. Our findings provide useful guidelines for researchers and insightful optimization advice for designing middlewares.

关键词： Embedded systems for robotic and automation software architecture for robotic and automation distributed robot systems

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Fields2Cover: An Open-Source Coverage Path Planning Library for Unmanned Agricultural Vehicles

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IEEE roboticS AND automation LETTERS 2023年第4期8卷 2166-2172页

作者： Mier, Gonzalo Valente, Joao de Bruin, Sytze Wageningen Univ & Res Lab Geoinformat Sci & Remote Sensing NL-6708 PB Wageningen Netherlands Wageningen Univ & Res Informat Technol Grp NL-6708 PB Wageningen Netherlands

This letter describes Fields2Cover, a novel open source library for coverage path planning (CPP) for agricultural vehicles. While there are several CPP solutions nowadays, there have been limited efforts to unify them into an open source library and provide benchmarking tools to compare their performance. Fields2Cover provides a framework for planning coverage paths, developing novel techniques, and benchmarking state-of-the-art algorithms. The library features a modular and extensible architecture that supports various vehicles and can be used for a variety of applications, including farms. Its core modules are: a headland generator, a swath generator, a route planner and a path planner. An interface to the Robot Operating System (ROS) is also supplied as an add-on. In this letter, the functionalities of the library for planning a coverage path in agriculture are demonstrated using 8 state-of-the-art methods and 7 objective functions in simulation and field experiments.

关键词： Libraries Linear programming Generators Robots Planning Path planning software algorithms Agricultural automation software architecture for robotic and automation field robots

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Improving the Reliability of Pick-and-Place With Aerial Vehicles Through Fault-Tolerant software and a Custom Magnetic End-Effector

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IEEE roboticS AND automation LETTERS 2021年第4期6卷 7501-7508页

作者： Garimella, Gowtham Sheckells, Matthew Kim, Soowon Baraban, Gabriel Kobilarov, Marin Johns Hopkins Univ Dept Mech Engn Baltimore MD 21218 USA Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA SpaceX Hawthorne CA 90250 USA Virginia Polytech Inst & State Univ Blacksburg VA 24061 USA

Aerial manipulation is an emerging field in robotics with various potential applications such as transport and delivery, agriculture, and, infrastructure inspection. To deploy aerial vehicles in the real world, the safety and reliability of these systems is paramount. Motivated by the need for safety and reliability, this work proposes a software framework that has built-in robustness to algorithmic failures and hardware faults. The framework allows users to build complex applications while reasoning about faults that can happen at different stages of an aerial manipulation task and specifying fallback actions to return to normal operating mode. The aerial manipulator is further endowed with a magnetic gripper that can handle positional errors arising from perception and control uncertainties. We also introduce a bias estimator for measuring the contact forces and sensor bias. We demonstrate how the estimator can be used to detect either completion or failures across several tasks. We demonstrate the reliability of the proposed framework on two tasks: package sorting task (e.g. as might be used in a distribution center) and sensor placement task (for infrastructure inspection). We show different failure modes that can occur and how our aerial manipulation system recovers from them.

关键词： Planning scheduling and coordination software architecture for robotic and automation factory automation

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ROS-NetSim: A Framework for the Integration of robotic and Network Simulators

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IEEE roboticS AND automation LETTERS 2021年第2期6卷 1120-1127页

作者： Calvo-Fullana, Miguel Mox, Daniel Pyattaev, Alexander Fink, Jonathan Kumar, Vijay Ribeiro, Alejandro Univ Penn Dept Elect & Syst Engn Philadelphia PA 19104 USA MIT Dept Aeronaut & Astronaut Cambridge MA 02139 USA Univ Penn Dept Mech Engn & Appl Mech Philadelphia PA 19104 USA Tampere Univ Unit Elect Engn Tampere 33720 Finland US Army Res Lab Dept Computat & Informat Sci Adelphi MD 20783 USA

Multi-agent systems play an important role in modern robotics. Due to the nature of these systems, coordination among agents via communication is frequently necessary. Indeed, Perception-Action-Communication (PAC) loops, or Perception-Action loops closed over a communication channel, are a critical component of multi-robot systems. However, we lack appropriate tools for simulating PAC loops. To that end, in this letter, we introduce ROS-NetSim, a ROS package that acts as an interface between robotic and network simulators. With ROS-NetSim, we can attain high-fidelity representations of both robotic and network interactions by accurately simulating the PAC loop. Our proposed approach is lightweight, modular and adaptive. Furthermore, it can be used with many available network and physics simulators by making use of our proposed interface. In summary, ROS-NetSim is (i) Transparent to the ROS target application, (ii) Agnostic to the specific network and physics simulator being used, and (iii) Tunable in fidelity and complexity. As part of our contribution, we have made available an open-source implementation of ROS-NetSim to the community.

关键词： Physics Robot kinematics Picture archiving and communication systems Synchronization Robot sensing systems Communication channels Wireless sensor networks Multi-robot systems networked robots methods and tools for robot system design software architecture for robotic and automation

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ChoiRbot: A ROS 2 Toolbox for Cooperative robotics

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IEEE roboticS AND automation LETTERS 2021年第2期6卷 2714-2720页

作者： Testa, Andrea Camisa, Andrea Notarstefano, Giuseppe Univ Bologna Dept Elect Elect & Informat Engn I-40136 Bologna Italy

In this letter, we introduce ChoiRbot, a toolbox for distributed cooperative robotics based on the novel Robot Operating System (ROS) 2. ChoiRbot provides a fully-functional toolset to execute complex distributed multi-robot tasks, either in simulation or experimentally, with a particular focus on networks of heterogeneous robots without a central coordinator. Thanks to its modular structure, ChoiRbot allows for a highly straight implementation of optimization-based distributed control schemes, such as distributed optimal control, model predictive control, task assignment, in which local computation and communication with neighboring robots are alternated. To this end, the toolbox provides functionalities for the solution of distributed optimization problems. The package can be also used to implement distributed feedback laws that do not need optimization features but do require the exchange of information among robots. The potential of the toolbox is illustrated with simulations and experiments on distributed robotics scenarios with mobile ground robots. The ChoiRbot toolbox is available at https://***/OPT4SMART/choirbot.

关键词： Distributed robot systems optimization and optimal control software architecture for robotic and automation

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VDMNav: software architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

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IEEE roboticS AND automation LETTERS 2024年第3期9卷 2869-2876页

作者： Laupre, Gabriel Francois Sharma, Aman Skaloud, Jan Ecole Polytech Fed Lausanne EPFL Environm Sensing Observ CH-1015 Lausanne Switzerland

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global Navigation Satellite System (GNSS), and other sensors, in a kinematic framework to yield a navigation solution (position, velocity, attitude, and time). However, the long-term accuracy of this solution is exacerbated during the absence of satellite positioning, especially for small drones with low-cost MEMS inertial sensors. On the other hand, a recently proposed vehicle dynamic model (VDM)-based navigation system has shown significant improvement in positioning accuracy during the absence of a satellite positioning solution, although in a mostly offline setting. In this article, we present the software architecture of its real-time implementation using Robot Operating System (ROS) that separates and interfaces its core from a particular hardware. The presented implementation asynchronously handles different sensor data in a modular fashion and allows i) adapting the underlying aerodynamic model, ii) including complementary sensors, and iii) reducing the dimensionality of the EKF state space at run-time without compromising the navigation performance. The real-time performance of the proposed software architecture is evaluated during long GNSS absences of up to eight minutes and compared to that of inertial coasting.

关键词： Field robots software architecture for robotic and automation software-hardware integration for robot systems

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