Remote Autonomy for Multiple Small Lowcost UAVs in GNSS-denied Search and Rescue Operations

2025-10-24

AI Summary

In GNSS-denied environments for search-and-rescue (SAR) operations, coordinating multiple low-cost UAVs remotely remains challenging due to reliance on skilled operators, high-end onboard hardware, and centralized infrastructure. Method: This paper proposes a lightweight, decentralized collaborative control framework. For the first time, it enables real-time visual-inertial odometry, lightweight obstacle detection, and distributed state estimation directly on the remote controller of unmodified consumer-grade DJI UAVs—implemented via an Android application that handles perception, decision-making, and multi-robot collaborative 3D mapping. Contribution/Results: The framework requires no onboard high-performance computing unit, no GNSS or specialized sensors, and no firmware-level modifications. It supports single-operator configuration, monitoring, and scheduling of heterogeneous UAV fleets. Experimental validation demonstrates robust autonomous multi-UAV flight and real-time 3D mapping in complex, unknown environments, significantly improving SAR operational efficiency and environmental perception robustness.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

In recent years, consumer-grade UAVs have been widely adopted by first responders. In general, they are operated manually, which requires trained pilots, especially in unknown GNSS-denied environments and in the vicinity of structures. Autonomous flight can facilitate the application of UAVs and reduce operator strain. However, autonomous systems usually require special programming interfaces, custom sensor setups, and strong onboard computers, which limits a broader deployment. We present a system for autonomous flight using lightweight consumer-grade DJI drones. They are controlled by an Android app for state estimation and obstacle avoidance directly running on the UAV's remote control. Our ground control station enables a single operator to configure and supervise multiple heterogeneous UAVs at once. Furthermore, it combines the observations of all UAVs into a joint 3D environment model for improved situational awareness.

Problem

• Enabling autonomous flight for consumer drones in GNSS-denied environments
• Overcoming sensor and computational limitations for multi-UAV operations
• Facilitating search and rescue missions with collaborative 3D mapping

Innovation

• Lightweight DJI drones for autonomous flight
• Android app on remote control for obstacle avoidance
• Single operator supervising multiple UAVs with joint 3D model