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Enhancing the Resilience of ROS 2-Based Multi-Robot Systems with Kubernetes: A Case Study on UWB-Based Relative

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Summary
This summary is machine-generated.

This study integrates Kubernetes with ROS 2 for robust multi-robot localization. The system demonstrates resilience against agent failures, crucial for applications like UWB-based relative positioning.

Keywords:
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Area of Science:

  • Robotics
  • Distributed Systems
  • Edge Computing

Background:

  • Robot Operating System (ROS) 2 is widely adopted for multi-robot applications, but deploying across heterogeneous hardware is challenging.
  • Tightly coordinated multi-agent systems, like Ultra-wideband (UWB)-based localization, are vulnerable to single-agent failures.
  • Kubernetes offers orchestration but its integration with ROS 2 for specific robotic applications needs evaluation.

Purpose of the Study:

  • To evaluate the integration of Kubernetes with ROS 2 for a UWB-based multi-robot localization system.
  • To assess the system's resilience and robustness against agent failures in a real-world deployment.
  • To demonstrate UWB ranging error mitigation using Long Short-Term Memory (LSTM) modules on edge nodes.

Main Methods:

  • An edge cluster was orchestrated using Kubernetes, comprising six NVIDIA Jetson Nano devices (one per robot) and a laptop.
  • ROS 2 applications were deployed on the edge nodes, including LSTM-based UWB ranging error mitigation modules.
  • Failures were systematically induced in various combinations of edge nodes and modules to test system response.

Main Results:

  • The integrated Kubernetes and ROS 2 system demonstrated resilience to individual agent and module failures.
  • Position errors were analyzed under different failure scenarios, quantifying the system's robustness.
  • The LSTM-based error mitigation effectively addressed UWB ranging errors in the multi-robot setup.

Conclusions:

  • Kubernetes orchestration enhances the deployment and management of ROS 2 applications in complex multi-robot systems.
  • The proposed system offers a robust solution for UWB-based relative localization, capable of tolerating agent failures.
  • This integration provides a scalable and resilient framework for advanced robotics research and deployment.