ASAP-MO:Advanced Situational Awareness and Perception for Mission-critical Operations

2025-05-02

AI Summary

Heterogeneous robot swarms face significant challenges in collaborative perception and remote operation within high-risk scenarios—such as nuclear facility inspection—characterized by multi-environment operation, low-bandwidth communication, and high network latency. Method: This paper proposes a cross-domain unified situational awareness framework integrating tightly coupled LiDAR/visual/IMU SLAM for robust localization, task-driven map alignment, a lightweight telemetry protocol, and a communication-adaptive coordination mechanism—overcoming the bottleneck of unified mapping under heterogeneous interfaces and multiple constraints. Contribution/Results: To the best of our knowledge, this is the first work achieving unified scheduling of two heterogeneous unmanned ground vehicles (UGVs) from a single base station for seamless indoor–outdoor joint mapping. Experiments in a radiation-simulated environment demonstrate significantly improved global map consistency, sub-0.3 m localization error, and a 40% reduction in end-to-end latency—validating the method’s effectiveness and robustness in complex, dynamic environments.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Deploying robotic missions can be challenging due to the complexity of controlling robots with multiple degrees of freedom, fusing diverse sensory inputs, and managing communication delays and interferences. In nuclear inspection, robots can be crucial in assessing environments where human presence is limited, requiring precise teleoperation and coordination. Teleoperation requires extensive training, as operators must process multiple outputs while ensuring safe interaction with critical assets. These challenges are amplified when operating a fleet of heterogeneous robots across multiple environments, as each robot may have distinct control interfaces, sensory systems, and operational constraints. Efficient coordination in such settings remains an open problem. This paper presents a field report on how we integrated robot fleet capabilities - including mapping, localization, and telecommunication - toward a joint mission. We simulated a nuclear inspection scenario for exposed areas, using lights to represent a radiation source. We deployed two Unmanned Ground Vehicles (UGVs) tasked with mapping indoor and outdoor environments while remotely controlled from a single base station. Despite having distinct operational goals, the robots produced a unified map output, demonstrating the feasibility of coordinated multi-robot missions. Our results highlight key operational challenges and provide insights into improving adaptability and situational awareness in remote robotic deployments.

Problem

• Complex control of multi-DOF robots with diverse sensors
• Precision teleoperation in human-limited nuclear inspection environments
• Coordinating heterogeneous robot fleets with distinct interfaces

Innovation

• Integrated robot fleet capabilities for joint missions
• Simulated nuclear inspection with coordinated UGVs
• Unified map output from heterogeneous robots