All-Onboard Relative Positioning and Control Framework for Autonomous Micro-UAV Swarms Based on Vision-Optoelectronic-UWB Fusion and Distributed Graph Optimization
Chengsong Xiong, Jiaqi Wan, Qifan Tong, Wenshuai Lu, Qingning He, Zheng You
AI summary
Problem
Existing micro-UAV swarm systems rely heavily on external infrastructure like GPS or high-end computing resources, preventing fully autonomous, lightweight operation at the gram scale.
Approach
The framework fuses onboard UWB, monocular vision, and optoelectronic sensors to measure inter-UAV distance and direction, then solves relative positions via distributed graph optimization and coordinates swarm movement using Voronoi diagrams for cooperative tracking.
Key results
- Achieved ~0.262 m relative localization accuracy for 150 g micro-UAVs without external aids
- Enabled ~100-meter autonomous outdoor formation flight and dynamic target encirclement
- Developed a lightweight multimodal sensing system consuming only 2.3 W per UAV
- Implemented a distributed Voronoi-based control strategy for real-time cooperative target tracking
Why it matters
This work enables fully autonomous, infrastructure-independent swarm operations for lightweight UAVs, advancing practical applications in search-and-rescue, surveillance, and swarm intelligence research.
Abstract
The autonomous cooperation of micro unmanned aerial vehicle (UAV) swarms remains a key challenge. Existing swarm relative positioning and control methods demand high sensing, computing, and communication resources and rely on external equipment like GPS and ground stations. To address these issues, this paper proposes an all-onboard and external- aiding-free swarm relative measurement, positioning and con- trol framework. The framework utilizes an onboard Vision- Optoelectronic-Ultra-Wideband (UWB) coupled measurement system to acquire inter-UAV relative distance and direction. Subsequently, the swarm’s relative positions are solved via a distributed graph optimization (DGO) approach. Based on the solved relative positions, swarm cooperative control is implemented through a distributed Voronoi diagram approach. Experimental results demonstrate that the proposed method enables 150 g micro-UAVs to achieve nearly 100-meter au- tonomous outdoor formation flight and collaborative tracking of dynamic targets, with swarm relative localization accuracy reaching approximately 0.262 m. This work pioneers fully autonomous measurement and control for 100-gram scale UAV swarms without external infrastructure, significantly advancing autonomy and enabling swarm intelligence emergence.