CSAR: Containerized System Architecture for Robotics

• URL: http://arxiv.org/abs/2606.30293v1
• Date: Mon, 29 Jun 2026 13:36:42 GMT
• Title: CSAR: Containerized System Architecture for Robotics
• Abstract summary: We present CSAR (Containerized System Architecture for Robotics), a container-centric architectural framework designed specifically for robotics teams and the edge-cloud.<n>CSAR combines LXC/LXD-based system containerization, ROS 2/DDS-based communication, and a three-layer edge infrastructure to organize computation into hardware-affine, persistent execution environments.<n>We describe a real deployment of CSAR in an academic robotics laboratory and evaluate it through representative use cases involving edge-offloaded 3D SLAM and GPU-accelerated semantic mapping.
• Score: 0.12045539806824919
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Robotic applications increasingly rely on distributed computational infrastructures that combine embedded devices, edge servers, and cloud resources. This evolution, together with the collaborative nature of robotics projects, has made the development, integration, deployment, and long-term operation of robotic systems significantly more complex. In practice, multi-user robotics software teams face persistent challenges related to dependency isolation, compatibility, reproducibility, efficient sharing of specialized hardware, and deployment across heterogeneous environments. In this paper, we present CSAR (Containerized System Architecture for Robotics), a container-centric architectural framework designed specifically for robotics teams and the edge-cloud continuum. CSAR combines LXC/LXD-based system containerization, ROS 2/DDS-based communication, and a three-layer edge infrastructure to organize computation into hardware-affine, persistent execution environments that remain decoupled from the volatility of experimental workloads. Through its Infrastructure Core, Platform and Multi-User Orchestration, and Compute and Acceleration layers, CSAR provides strong isolation, controlled resource sharing, and topology-aware networking for distributed robotic applications. To demonstrate its validity, we describe a real deployment of CSAR in an academic robotics laboratory and evaluate it through representative use cases involving edge-offloaded 3D SLAM and GPU-accelerated semantic mapping. The results indicate that CSAR simplifies software integration, improves the utilization of shared computational resources, and facilitates safe prototyping, as well as reproducible and collaborative experimentation in robotics teams. The implementation described in this paper, including deployment templates, configuration files, and documentation, is available at https://github.com/goyoambrosio/CSAR.

Related papers

• CoAdapt: An LLM-based Framework for Adaptive Collaborative Perception in IIoT Robotic Swarms [2.6155698073666023]
  CoAdapt is an adaptive collaborative perception framework for IIoT robotic swarms.<n>Our approach achieves a 38% reduction in communication cost while maintaining detection precision comparable to static baseline approaches.
  arXiv  Detail & Related papers  (2026-09-15T08:44:08Z)
• CoEnv: Driving Embodied Multi-Agent Collaboration via Compositional Environment [54.84167973913561]
  CoEnv is a framework that leverages simulation for safe strategy exploration while ensuring reliable real-world deployment.<n>CoEnv operates through three stages: real-to-sim scene reconstruction that digitizes physical workspaces, VLM-driven action synthesis supporting both real-time planning with code-based trajectory generation, and validated sim-to-real transfer with collision detection for safe deployment.
  arXiv  Detail & Related papers  (2026-04-07T06:24:41Z)
• Environment-Grounded Multi-Agent Workflow for Autonomous Penetration Testing [0.0]
  This paper explores the use of large language models for automated penetration testing in robotic environments.<n>We propose an environment-grounded multi-agent architecture tailored to Robotics-based systems.
  arXiv  Detail & Related papers  (2026-03-25T11:50:08Z)
• RSLCPP -- Deterministic Simulations Using ROS 2 [4.815503491342169]
  Simulation is crucial in real-world robotics, offering safe, scalable, and efficient environments for developing applications.<n>We present a methodology to create deterministic simulations using ROS 2 nodes.<n>Our approach yields identical results when testing both a synthetic benchmark and a real-world robotics system.
  arXiv  Detail & Related papers  (2026-01-11T20:10:54Z)
• A Unified AI, Embedded, Simulation, and Mechanical Design Approach to an Autonomous Delivery Robot [0.0]
  This paper presents the development of a fully autonomous delivery robot integrating mechanical engineering, embedded systems, and artificial intelligence.<n>The platform employs a heterogeneous computing architecture, with RPi 5 and ROS 2 handling AI-based perception and path planning.<n>The mechanical design was optimized for payload capacity and mobility through precise motor selection and material engineering.
  arXiv  Detail & Related papers  (2025-12-26T23:39:54Z)
• A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks [49.90474228895655]
  Cloud-edge-terminal collaborative intelligence (CETCI) is a fundamental paradigm within the artificial intelligence of things (AIoT) community.<n>CETCI has made significant progress with emerging AIoT applications, moving beyond isolated layer optimization to deployable collaborative intelligence systems.<n>This survey describes foundational architectures, enabling technologies, and scenarios of CETCI paradigms, offering a tutorial-style review for CISAIOT beginners.
  arXiv  Detail & Related papers  (2025-08-26T08:38:01Z)
• ROS-related Robotic Systems Development with V-model-based Application of MeROS Metamodel [0.49259062564301753]
  Systems built on the Robot Operating System (ROS) are increasingly easy to assemble, yet hard to govern and reliably coordinate.<n>In this paper, we use a compact heterogeneous robotic system (HeROS), combining mobile and manipulation capabilities, as a demonstration vehicle.<n>We propose a structured methodology based on MeROS - a SysML metamodel created specifically to put the ROS-based systems into the focus of the Model-Based Systems Engineering (MBSE) workflow.
  arXiv  Detail & Related papers  (2025-06-10T11:44:00Z)
• CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground Environments [38.264929235624905]
  CompSLAM is a multi-modal localization and mapping framework for robots.<n>It was deployed on all aerial, legged, and wheeled robots of Team Cerberus during their competition-winning final run.<n>This paper also introduces a dataset acquired by a manually teleoperated quadrupedal robot, covering a significant portion of the DARPA Subterranean Challenge finals course.
  arXiv  Detail & Related papers  (2025-05-10T00:59:31Z)
• RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation [77.41969287400977]
  This paper presents textbfRobotScript, a platform for a deployable robot manipulation pipeline powered by code generation. We also present a benchmark for a code generation benchmark for robot manipulation tasks in free-form natural language. We demonstrate the adaptability of our code generation framework across multiple robot embodiments, including the Franka and UR5 robot arms.
  arXiv  Detail & Related papers  (2024-02-22T15:12:00Z)
• LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Control [72.81786007015471]
  We propose a learnable Perception-Action-Communication (LPAC) architecture for the problem.<n>CNN processes localized perception; a graph neural network (GNN) facilitates robot communications.<n> Evaluations show that the LPAC models outperform standard decentralized and centralized coverage control algorithms.
  arXiv  Detail & Related papers  (2024-01-10T00:08:00Z)
• Towards AIOps in Edge Computing Environments [60.27785717687999]
  This paper describes the system design of an AIOps platform which is applicable in heterogeneous, distributed environments. It is feasible to collect metrics with a high frequency and simultaneously run specific anomaly detection algorithms directly on edge devices.
  arXiv  Detail & Related papers  (2021-02-12T09:33:00Z)
• Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents [61.36681529571202]
  We describe a new concept for reproducible robotics research that integrates development and benchmarking. One of the central components of this setup is the Duckietown Autolab, a standardized setup that is itself relatively low-cost and reproducible. We validate the system by analyzing the repeatability of experiments conducted using the infrastructure and show that there is low variance across different robot hardware and across different remote labs.
  arXiv  Detail & Related papers  (2020-09-09T15:31:29Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.