CORTEXA
← Browse
arxivcs.RO2026-07-22

Decentralized UAV Swarms for Ground Target Protection in GPS- and Communication-Denied Environments

Dimitria Silveria, Paulo Ricardo Marques de Araujo, Tiago Nascimento, Sidney Givigi

The presence of UAVs in military operations has recently increased, also increasing the demand for defense systems against UAV attacks. UAVs can also be used as countermeasures. Most available methods rely on UAV-to-UAV communication and global positioning. However, such resources may not be available in modern warfare scenarios. To address these limitations, we propose a pipeline for ground-target protection against UAV attacks that employs autonomous swarms of UAVs. We assume a communication- and GPS-denied environment in which the UAVs use onboard sensors to track the target and coordinate as a swarm. We developed Kalman filters to estimate the states of unknown targets and the positions of UAVs in the swarm using only relative measurements. Also, our strategy is to encircle the target of interest to maximize coverage. To achieve that, we propose a decentralized swarm encirclement technique that adapts to the target's motion. Our approach was extensively validated using real robots, demonstrating its effectiveness in detecting, encircling, and intercepting hostile UAVs.

View free PDFSource page

Related papers

arxivcs.ROcs.CV2026-07-21

NGPS: GPS-Denied Aerial Geo-Localization and 2.5D Reconstruction via Deep Satellite Image Matching and Multi-Rate Sensor Fusion

Sanket Sharma

We present NGPS (Next-Generation Positioning System), a visual geo-localization framework for high-altitude UAVs that provides GPS-free absolute positioning by matching down-facing images to georeferenced satellite imagery with deep features. The system combines (1) adaptive conf…

View free PDFSource page
arxivcs.RO2026-07-16

CosFly-VLA: A Spatially Aware Vision-Language-Action Model for UAV Tracking

Ruilong Ren, Songsheng Cheng, Yunpeng Zhou, Hanxuan Chen, Xiangyue Wang, Tianle Zeng, et al.

Dynamic target tracking is essential for Unmanned Aerial Vehicles (UAVs) operating in complex urban environments, where both the target and the camera viewpoint change continuously. Existing Vision-Language-Action (VLA) policies can track visible targets effectively, but their pe…

View free PDFSource page
arxivcs.RO2026-07-17

Implicit Virtual Leader: Decentralized Vision-Only Relative Pose Estimation for Multi-Robot Formations

Shiyuan Yang, Zelin Wang, Zhijia Tao, Yilin Wang, Zhengyu Hou, Xiaosong Kong, et al.

Classical leader-follower formation control suffers from single points of failure and error propagation, and relies on absolute localization sensors that are ill-suited for GPS-denied environments. We address these limitations by introducing a fully decentralized, vision-only rel…

View free PDFSource page
arxivcs.ITcs.LGcs.RO2026-07-21

CRB-Driven Beamforming and Trajectory Optimization for UAV-assisted ISAC System

Yi Yang, Qianqian Zhang, Huaxia Wang

In this paper, we study an unmanned aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) system, where a UAV enhances the sensing capability of a base station (BS) towards a target while ensuring reliable communication towards a downlink user. This architectu…

View free PDFSource page
arxivcs.ROeess.SY2026-07-31

MROPE: A Multi-Robot Safe Cooperative Strategy via combined Predictive Safety Filters and Ellipse-based Constraint Compression

Alice Rosetti, Lorenzo Pichierri, Domenico Cappello, Fabrizio Schiano, Giuseppe Notarstefano

Deploying drone swarms to track a dynamic target in cluttered environments presents severe computational and safety challenges. We propose MROPE, a hierarchical strategy that decouples the cooperative monitoring mission from strict local safety requirements. To overcome the compu…

View free PDFSource page
arxivcs.ROcs.AI2026-07-23

VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method

Jiabin Lou, Haopeng Wang, Yuanshuai Wang, Xinyu Liu, Xuxin Lv, Yuxin Guo, et al.

Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions. However, route-level instructions commonly encode spatial priors, such as orientation, distance, and layout, that are not explicitly available from onboard sensing at deployment…

View free PDFSource page