Real-Time Resource Allocation for ROS2-based Safety-Critical Systems using Model Predictive Control

• Author(s): Sudharsan Vaidhun Bhaskar ; Dr. Ravinder Kumar
• Paper ID: 1706511
• Page: 952-980
• Published Date: 26-12-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 5 November-2024

Abstract

Real-time resource allocation in safety-critical systems is a significant challenge, particularly in the context of robotics. In this paper, we propose a novel framework for resource allocation in Robot Operating System 2 (ROS2)-based systems, which are often employed in safety-critical applications such as autonomous vehicles and industrial robots. The framework integrates Model Predictive Control (MPC) to optimize resource distribution in real-time, ensuring the system's safety and operational efficiency. MPC is employed due to its ability to handle constraints and dynamically adjust resources to meet both system requirements and safety specifications. The proposed method aims to address issues such as computational load balancing, energy efficiency, and fault tolerance, which are critical in environments where failure is not an option. Through the use of predictive models, the approach anticipates future system demands and adjusts resources proactively, reducing the risk of resource exhaustion and improving the system's ability to react to unexpected conditions. The paper also discusses how this methodology integrates seamlessly into ROS2, benefiting from its real-time capabilities and robust communication infrastructure. Simulation results demonstrate the effectiveness of the proposed resource allocation strategy, highlighting improvements in system responsiveness and safety under varying operational conditions. This approach is particularly applicable to mission-critical robotics applications where both reliability and real-time performance are paramount, such as in healthcare, automotive, and industrial automation sectors. The proposed model offers a promising solution for enhancing the operational safety and efficiency of ROS2-based systems in dynamic and resource-constrained environments.

Keywords

Real-time resource allocation, ROS2, safety-critical systems, Model Predictive Control, resource optimization, autonomous systems, computational load balancing, energy efficiency, fault tolerance, predictive modeling, system performance, real-time capabilities, robotics.

Citations

IRE Journals:
Sudharsan Vaidhun Bhaskar , Dr. Ravinder Kumar "Real-Time Resource Allocation for ROS2-based Safety-Critical Systems using Model Predictive Control" Iconic Research And Engineering Journals Volume 8 Issue 5 2024 Page 952-980

IEEE:
Sudharsan Vaidhun Bhaskar , Dr. Ravinder Kumar "Real-Time Resource Allocation for ROS2-based Safety-Critical Systems using Model Predictive Control" Iconic Research And Engineering Journals, 8(5)