GLIDE: A Coordinated Aerial-Ground Framework for Search and Rescue in Unknown Environments

2025-09-17

AI Summary

To address the challenges of rapid victim localization and safe navigation in unknown environments for search-and-rescue (SAR) missions, this paper proposes GLIDE—a heterogeneous multi-robot collaborative framework comprising two unmanned aerial vehicles (UAVs) and one unmanned ground vehicle (UGV). One UAV performs wide-area target detection and georeferenced localization; the second, forward-flying UAV senses terrain traversability in real time and provides long-horizon navigational guidance; the UGV fuses aerial and ground multimodal sensory data to execute continuous A* re-planning and dynamic obstacle avoidance. Key innovations include a role-separation architecture, a long-horizon guidance planning mechanism, and a mid-layer traversability feedback loop. Experiments on both physical platforms and high-fidelity simulation demonstrate significant improvements: average arrival time reduced by 32.7%, and collision rate decreased by 78.5%, validating GLIDE’s enhanced SAR efficiency and robustness in complex, unstructured environments.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Learning to Search

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We present a cooperative aerial-ground search-and-rescue (SAR) framework that pairs two unmanned aerial vehicles (UAVs) with an unmanned ground vehicle (UGV) to achieve rapid victim localization and obstacle-aware navigation in unknown environments. We dub this framework Guided Long-horizon Integrated Drone Escort (GLIDE), highlighting the UGV's reliance on UAV guidance for long-horizon planning. In our framework, a goal-searching UAV executes real-time onboard victim detection and georeferencing to nominate goals for the ground platform, while a terrain-scouting UAV flies ahead of the UGV's planned route to provide mid-level traversability updates. The UGV fuses aerial cues with local sensing to perform time-efficient A* planning and continuous replanning as information arrives. Additionally, we present a hardware demonstration (using a GEM e6 golf cart as the UGV and two X500 UAVs) to evaluate end-to-end SAR mission performance and include simulation ablations to assess the planning stack in isolation from detection. Empirical results demonstrate that explicit role separation across UAVs, coupled with terrain scouting and guided planning, improves reach time and navigation safety in time-critical SAR missions.

Problem

• Cooperative aerial-ground search-and-rescue in unknown environments
• Rapid victim localization with obstacle-aware navigation
• Multi-UAV coordination for improved reach time and safety

Innovation

• Cooperative aerial-ground search-and-rescue framework
• UAVs provide victim detection and terrain scouting
• UGV fuses aerial cues with local sensing