One Operator, Many Robots: Natural-Language Command of UAV–UGV Teams for Search, Victim Detection, and Rescue Under review
IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) 2026
A real-world SAR extension of Swarm-Steward that connects multi-UAV search, live aerial victim detection, geolocation, operator confirmation, and UGV deployment — one operator voice-commands the whole team. Evaluated in 12 outdoor experiments over a 47,362 m² unstructured area with one-, two-, and four-UAV teams, achieving best victim-localization errors of 1.21–2.29 m, with feedback from a professional firefighter.
Swarm-Steward: Scalable and Reliable Natural-Language Coordination of Autonomous Aerial and Ground Robots
2026 International Conference on Unmanned Aircraft Systems (ICUAS) 2026
A platform-agnostic hierarchical LLM multi-agent system that lets a non-expert operator coordinate swarms of aerial and ground robots through natural language. It separates planning and grounding from a safety-gated deterministic execution stage, uses dual retrieval-augmented generation (map-feature + telemetry), keeps token cost near-constant from 5 to 500 drones, achieves 92.9% task success, and validates sim-to-real transfer on a DJI Mini 4 Pro swarm.
Real-World Deployment of an LLM-Enabled Voice-Commanded UGV for Logistics in SAR Missions
2025 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) 2025
Deploys an LLM-enabled voice-command interface on a UGV for logistics support in search-and-rescue missions, letting operators without robotics expertise issue natural-language voice commands that the robot grounds in real-time mission data for safe, context-aware navigation.
SAREnv: An Open-Source Dataset and Benchmark Tool for Informed Wilderness Search and Rescue Using UAVs
Drones (MDPI) 2025
An open-access dataset and evaluation framework for benchmarking UAV-based wilderness search-and-rescue planning algorithms — shared infrastructure developed under the NAMUR project umbrella (in collaboration with the WildDrone/HERD teams).