Air-Ground Collaborative Robots for Fire and Rescue Missions: Towards Mapping and Navigation Perspective

TL;DR

The paper investigates air‑ground collaborative robots for fire and rescue by focusing on mapping and navigation as the core enablers of autonomous cooperation between UAVs and UGVs. It introduces a UAV‑map/UGV‑navigation framework, systematically surveys 2‑D, 3‑D, topological, and semantic map types, and analyzes co‑localization and navigation strategies across map modalities. The work classifies collaboration schemes by the numbers of UAVs and UGVs and discusses representative applications and challenges, offering case studies to illustrate practical impact. It highlights opportunities in mission‑oriented UAV mapping, multi‑modal data fusion, and embodied AI‑driven navigation to enhance rescue efficiency and operator safety.

Abstract

Air-ground collaborative robots have shown great potential in the field of fire and rescue, which can quickly respond to rescue needs and improve the efficiency of task execution. Mapping and navigation, as the key foundation for air-ground collaborative robots to achieve efficient task execution, have attracted a great deal of attention. This growing interest in collaborative robot mapping and navigation is conducive to improving the intelligence of fire and rescue task execution, but there has been no comprehensive investigation of this field to highlight their strengths. In this paper, we present a systematic review of the ground-to-ground cooperative robots for fire and rescue from a new perspective of mapping and navigation. First, an air-ground collaborative robots framework for fire and rescue missions based on unmanned aerial vehicle (UAV) mapping and unmanned ground vehicle (UGV) navigation is introduced. Then, the research progress of mapping and navigation under this framework is systematically summarized, including UAV mapping, UAV/UGV co-localization, and UGV navigation, with their main achievements and limitations. Based on the needs of fire and rescue missions, the collaborative robots with different numbers of UAVs and UGVs are classified, and their practicality in fire and rescue tasks is elaborated, with a focus on the discussion of their merits and demerits. In addition, the application examples of air-ground collaborative robots in various firefighting and rescue scenarios are given. Finally, this paper emphasizes the current challenges and potential research opportunities, rounding up references for practitioners and researchers willing to engage in this vibrant area of air-ground collaborative robots.

Figures (20)

• Figure 1: Illustration of air-ground collaborative robots framework for fire and rescue missions based on UAV mapping and UGV navigation.
• Figure 2: Schematic of the relationship between air-ground collaborative robots for map construction and navigation.
• Figure 3: Experimental scenario of UAV-guided UGVs navigation, where the UAV provides environment perception and mapping for UGVs to avoid potential collisions li2023colag.
• Figure 4: Scenario of the parcel delivery task with UGV based on OctoMap built by UAV arbanas2018decentralized.
• Figure 5: A topological map of the 3-D environment that is constructed incrementally as the UAV flies within the sensor range wang2020efficient.