Enhancing Cellular-enabled Collaborative Robots Planning through GNSS data for SAR Scenarios

TL;DR

This paper presents a novel SAR planning framework that optimizes robot deployment and paths by leveraging GNSS and mobile network data, improving efficiency and connectivity in rescue scenarios.

Contribution

It introduces a comprehensive SAR framework integrating mission planning with environmental and network data to optimize robot deployment and operation.

Findings

Trade-offs between robot number, area coverage, and response time analyzed.

Terrain elevation data significantly impacts mission time and energy consumption.

Incorporating environmental factors improves mobile connectivity and operational efficiency.

Abstract

Cellular-enabled collaborative robots are becoming paramount in Search-and-Rescue (SAR) and emergency response. Crucially dependent on resilient mobile network connectivity, they serve as invaluable assets for tasks like rapid victim localization and the exploration of hazardous, otherwise unreachable areas. However, their reliance on battery power and the need for persistent, low-latency communication limit operational time and mobility. To address this, and considering the evolving capabilities of 5G/6G networks, we propose a novel SAR framework that includes Mission Planning and Mission Execution phases and that optimizes robot deployment. By considering parameters such as the exploration area size, terrain elevation, robot fleet size, communication-influenced energy profiles, desired exploration rate, and target response time, our framework determines the minimum number of robots required and their optimal paths to ensure effective coverage and timely data backhaul over mobile networks. Our results demonstrate the trade-offs between number of robots, explored area, and response time for wheeled and quadruped robots. Further, we quantify the impact of terrain elevation data on mission time and energy consumption, showing the benefits of incorporating real-world environmental factors that might also affect mobile signal propagation and connectivity into SAR planning. This framework provides critical insights for leveraging next-generation mobile networks to enhance autonomous SAR operations.