SERN: Simulation-Enhanced Realistic Navigation for Multi-Agent Robotic Systems in Contested Environments

2024-10-22

arXiv.org

AI Summary

To address the challenges of real-time collaborative decision-making and asset coordination for multi-robot navigation in adversarial and complex environments, this paper proposes a cyber-physical integrated real-time decision framework. The framework employs a bidirectional ROS bridge to achieve high-fidelity motion synchronization and cross-domain communication between physical and virtual robots; introduces a multi-objective cost function that dynamically balances communication latency, reliability, and bandwidth; and provides theoretical proof of bounded cyber-physical positional error. It further pioneers a perception-navigation paradigm integrating Unity-based high-fidelity simulation with semantic segmentation (YOLO/SegFormer). Experiments demonstrate sub-5 cm positional and sub-2° orientation synchronization errors between physical and virtual robots; 15–24% end-to-end latency reduction and 15% throughput improvement over conventional ROS-based approaches; and successful validation on heterogeneous multi-robot systems comprising Jackal and Husky platforms.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Multiagent Systems: Coordination and Collaboration
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

The increasing deployment of autonomous systems in complex environments necessitates efficient communication and task completion among multiple agents. This paper presents SERN (Simulation-Enhanced Realistic Navigation), a novel framework integrating virtual and physical environments for real-time collaborative decision-making in multi-robot systems. SERN addresses key challenges in asset deployment and coordination through our bi-directional SERN ROS Bridge communication framework. Our approach advances the SOTA through: accurate real-world representation in virtual environments using Unity high-fidelity simulator; synchronization of physical and virtual robot movements; efficient ROS data distribution between remote locations; and integration of SOTA semantic segmentation for enhanced environmental perception. Additionally, we introduce a Multi-Metric Cost Function (MMCF) that dynamically balances latency, reliability, computational overhead, and bandwidth consumption to optimize system performance in contested environments. We further provide theoretical justification for synchronization accuracy by proving that the positional error between physical and virtual robots remains bounded under varying network conditions. Our evaluations show a 15% to 24% improvement in latency and up to a 15% increase in processing efficiency compared to traditional ROS setups. Real-world and virtual simulation experiments with multiple robots (Clearpath Jackal and Husky) demonstrate synchronization accuracy, achieving less than $5 ext{ cm}$ positional error and under $2^circ$ rotational error. These results highlight SERN's potential to enhance situational awareness and multi-agent coordination in diverse, contested environments.

Problem

• Enhances multi-agent coordination in contested environments.
• Improves real-time decision-making through virtual-physical integration.
• Optimizes system performance with dynamic cost balancing.

Innovation

• Integrates Unity simulator for real-world representation
• Synchronizes physical and virtual robot movements
• Uses Multi-Metric Cost Function for performance optimization