Paper Reading AI Learner

Precision Meets Art: Autonomous Multi-UAV System for Large Scale Mural Drawing

2026-01-10 10:00:23
Andrei A. Korigodskii, Artem E. Vasiunik, Georgii A. Varin, Adilia M. Zukhurova, Matvei V. Urvantsev, Semen A. Osipenkov, Igor S. Efremov, Georgii E. Bondar

Abstract

The integration of autonomous unmanned aerial vehicles (UAVs) into large-scale artistic projects has emerged as a new application in robotics. This paper presents the design, deployment, and testing of a novel multi-drone system for automated mural painting in outdoor settings. This technology makes use of new software that coordinates multiple drones simultaneously, utilizing state-machine algorithms for task execution. Key advancements are the complex positioning system that combines 2D localization using a single motion tracking camera with onboard LiDAR for precise positioning, and a novel flight control algorithm, which works differently along the trajectory and normally to it, ensuring smoothness and high precision of the drawings at the same time. A 100 square meters mural was created using the developed multi-drone system, validating the system's efficacy. Compared to single-drone approaches, our multi-UAV solution significantly improves scalability and operational speed while maintaining high stability even in harsh weather conditions. The findings highlight the potential of autonomous robotic swarms in creative applications, paving the way for further advancements in large-scale robotic art.

Abstract (translated)

将自主无人飞行器(UAV)集成到大型艺术项目中,已成为机器人技术的一个新应用领域。本文介绍了设计、部署和测试一种新型多无人机系统以在户外环境下进行自动化壁画绘制的过程。该技术利用新的软件来同时协调多个无人机的操作,并采用状态机算法执行任务。 关键技术进步包括一个复杂的定位系统,结合使用单个运动跟踪相机进行二维定位与机载LiDAR相结合的精确位置确定方法,以及一种全新的飞行控制算法,这种算法在轨迹上和正常操作中工作方式不同,确保绘制图形的同时具备流畅性和高精度。利用开发的多无人机系统成功创作了一幅100平方米大小的壁画,验证了该系统的有效性。 与单个无人机的方法相比,我们的多UAV解决方案显著提高了可扩展性以及运行速度,并且即使在恶劣天气条件下也能保持高度稳定性。研究结果突显了自主机器人集群在创意应用中的潜力,为大规模机器人艺术的发展铺平道路。

URL

https://arxiv.org/abs/2601.06508

PDF

https://arxiv.org/pdf/2601.06508.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model LLM Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Robot Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Time_Series Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot