MCS-Sim: A Photo-Realistic Simulator for Multi-Camera UAV Visual Perception Research

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Publicado en:Drones vol. 9, no. 9 (2025), p. 656-681
Autor principal: Qi Qiming
Otros Autores: Wang Guoyan, Pan Yonglei, Fan Hongqi, Li, Biao
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MDPI AG
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022 |a 2504-446X 
024 7 |a 10.3390/drones9090656  |2 doi 
035 |a 3254504457 
045 2 |b d20250101  |b d20251231 
100 1 |a Qi Qiming 
245 1 |a MCS-Sim: A Photo-Realistic Simulator for Multi-Camera UAV Visual Perception Research 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Multi-camera systems (MCSs) are pivotal in aviation surveillance and autonomous navigation due to their wide coverage and high-resolution sensing. However, challenges such as complex setup, time-consuming data acquisition, and costly testing hinder research progress. To address these, we introduce MCS-Sim, a photo-realistic MCS simulator for UAV visual perception research. MCS-Sim integrates vision sensor configurations, vehicle dynamics, and dynamic scenes, enabling rapid virtual prototyping and multi-task dataset generation. It supports dense flow estimation, 3D reconstruction, visual simultaneous localization and mapping, object detection, and tracking. With a hardware-in-loop interface, MCS-Sim facilitates closed-loop simulation for system validation. Experiments demonstrate its effectiveness in synthetic dataset generation, visual perception algorithm testing, and closed-loop simulation. Here we show that MCS-Sim significantly advances multi-camera UAV visual perception research, offering a versatile platform for future innovations. 
653 |a Simultaneous localization and mapping 
653 |a Accuracy 
653 |a Datasets 
653 |a Virtual prototyping 
653 |a Data acquisition 
653 |a Visual perception 
653 |a Hardware-in-the-loop simulation 
653 |a Cameras 
653 |a Closed loops 
653 |a Unmanned aerial vehicles 
653 |a Three dimensional flow 
653 |a Engines 
653 |a Localization 
653 |a Virtual reality 
653 |a Visual perception driven algorithms 
653 |a Simulation 
653 |a Physics 
653 |a Image reconstruction 
653 |a Computer vision 
653 |a Sensors 
653 |a Autonomous navigation 
653 |a Algorithms 
653 |a Semantics 
653 |a Synthetic data 
700 1 |a Wang Guoyan 
700 1 |a Pan Yonglei 
700 1 |a Fan Hongqi 
700 1 |a Li, Biao 
773 0 |t Drones  |g vol. 9, no. 9 (2025), p. 656-681 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3254504457/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3254504457/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3254504457/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch