OPsCV: A Robust Framework for Aerial Navigation under Global Positioning System Denied Conditions
DOI:
https://doi.org/10.1590/jatm.v18.1413Keywords:
Unmanned Aerial Vehicle, Inertial-visual navigation, Air-ground collaboration, Deep inertial odometry, Cross-view geolocalizationAbstract
Unmanned aerial vehicles (UAVs) rely heavily on the global navigation satellite system (GNSS) for accurate localization. However, GNSS signals are often unavailable or unreliable in contested or cluttered environments. This study presents the optimized pose prediction and cross-view (OPsCV), a robust and adaptable navigation framework that integrates deep inertial odometry with a simulated cross-view geolocalization module through an error-state Kalman filter. The system enables dynamic switching from GNSS-based positioning to a fused solution that combines inertial and vision-based estimates as GNSS signal quality degrades. The framework was evaluated using real UAV flight data under persistent GNSS denial, with results demonstrating reliable pose estimation and improved positioning accuracy compared to the UAV’s internal navigation system. The OPsCV method maintained performance even with sparse cross-view updates, confirming its resilience under conservative operational conditions. These findings highlight the potential of fusing learned inertial measurements with statistical vision-based localization for autonomous aerial navigation in GNSS-denied environments.
References
[DJI] Dà-Jiāng Innovations (2022) Matrice 600 Pro. https://www.dji.com/br/matrice600-pro
[GSI] Gabinete de Segurança Institucional (2023) Release do Exercício Geral Integrado de Resposta à Emergência e Segurança Física Nuclear em Angra dos Reis. In Portuguese. https://www.gov.br/gsi/pt-br/centrais-de-conteudo/noticias/2023-1/release-doexercicio-geral-integrado-de-resposta-a-emergencia-e-seguranca-fisica-nuclear-em-angra-dos-reis-1
Afraimovich EL, Lesyuta OS, Ushakov II (2000) Magnetospheric disturbances, and the GPS operation. https://arxiv.org/abs/physics/0009027
Allauddin MS, Kiran GS, Raj K, Srinivas G, Mouli GUR, Prasad PV (2019) Development of a surveillance system for forest fire detection and monitoring using drones. Paper presented 2019 IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE; Yokohama, Japan. https://doi.org/10.1109/IGARSS.2019.8900436
Almeida DRA, Broadbent E, Zambrano AMA, Ferreira MP, Brancalion PHS (2021) Fusion of LiDAR and hyperspectral data from drones for ecological questions: The GatorEye Atlantic Forest restoration case study. Paper presented 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE; Brussels, Belgium. https://doi.org/10.1109/IGARSS47720.2021.9554023
Al-Sharman MK, Zweiri Y, Jaradat MA, Al-Husari R, Gan D, Seneviratne LD (2020) Deep-learning-based neural network training for state estimation enhancement: Application to attitude estimation. IEEE Trans Instrum Meas 69(1):24-34. https://doi.org/10.1109/tim.2019.2895495
Balaska V, Bampis L, Gasteratos A (2022) Self-localization based on terrestrial and satellite semantics. Eng Appl Artif Intell 111:104824. https://doi.org/10.1016/J.ENGAPPAI.2022.104824
Berntorp K, Hoang T, Di Cairano S (2019) Motion planning of autonomous road vehicles by particle filtering. IEEE Trans Intell Veh 4(2):197-210. https://doi.org/10.1109/TIV.2019.2904394
Bhowmick J, Singh A, Gupta H, Nallanthighal R (2021) A novel approach to computationally lighter GNSS denied UAV navigation using monocular camera. Paper presented 2021 7th International Conference on Automation, Robotics and Applications (ICARA). IEEE; Prague, Czech Republic. https://doi.org/10.1109/ICARA51699.2021.9376502
Brossard M, Barrau A, Bonnabel S (2019) RINS-W: Robust inertial navigation system on wheels. Paper presented 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE; Macau, China. https://doi.org/10.1109/iros40897.2019.8968593
Brossard M, Barrau A, Bonnabel S (2020) AI-IMU dead-reckoning. IEEE Trans Intell Veh 5(4):585-595. https://doi.org/10.1109/tiv.2020.2980758
Buchanan R, Camurri M, Dellaert F, Fallon M (2021) Learning inertial odometry for dynamic legged robot state estimation. Paper presented 2021 5th Conference on Robot Learning. PMLR; London, UK. https://doi.org/10.48550/ARXIV.2111.00789
Burri M, Nikolic J, Gohl P, Schneider T, Rehder J, Omari S, Achtelik MW, Siegwart R (2016) The EuRoC micro aerial vehicle datasets. Int J Robot Res 35(10):1157-1163. https://doi.org/10.1177/0278364915620033
Cao R, Zhu J, Tu W, Li Q, Cao J, Liu B, Zhang Q, Qiu G (2018) Integrating aerial and street view images for urban land use classification. Remote Sens 10(10):1553. https://doi.org/10.3390/RS10101553
Carrillo-Arce LC, Nerurkar ED, Gordillo JL, Roumeliotis SI (2013) Decentralized multi-robot cooperative localization using covariance intersection. Paper presented 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE; Tokyo, Japan. https://doi.org/10.1109/iros.2013.6696534
Chang Y, Cheng Y, Manzoor U, Murray J (2023) A review of UAV autonomous navigation in GPS-denied environments. Robot Auton Syst 170:104533. https://doi.org/10.1016/j.robot.2023.104533
Chen C, Lu X, Markham A, Trigoni N (2018a) IONet: Learning to cure the curse of drift in inertial odometry. Proc AAAI Conf Artif Intell 32(1). https://doi.org/10.1609/aaai.v32i1.12102
Chen C, Miao Y, Lu CX, Xie L, Blunsom P, Markham A, Trigoni N (2019) MotionTransformer: Transferring neural inertial tracking between domains. Proc AAAI Conf Artif Intell 33(1):8009-8016. https://doi.org/10.1609/aaai.v33i01.33018009
Chen C, Pan X (2024) Deep learning for inertial positioning: A survey. IEEE Trans Intell Transp Syst 25(9):10506-10523. https://doi.org/10.1109/tits.2024.3381161
Chen C, Zhao P, Lu CX, Wang W, Markham A, Trigoni N (2018b) OxIOD: The dataset for deep inertial odometry. https://arxiv.org/abs/1809.07491
Chiella ACB, Teixeira BOS, Pereira GAS (2019) State estimation for aerial vehicles in forest environments. Paper presented 2019 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE; Atlanta, USA. https://doi.org/10.1109/
Chui CK, Chen G (2017) Kalman filtering. Cham: Springer. https://doi.org/10.1007/978-3-319-47612-4
Cobb S, Lawrence D, Christie J, Walter T, Chao YC, Powell D, Parkinson B (1995) Observed GPS signal continuity interruptions. Paper presented 1995 Proceedings of Ion GPS. Institute of Navigation; California, EUA.
Cohen N, Klein I (2024) Inertial navigation meets deep learning: A survey of current trends and future directions. Results Eng 24:103565. https://doi.org/10.1016/j.rineng.2024.103565
Cortes S, Solin A, Kannala J (2018) Deep learning based speed estimation for constraining strapdown inertial navigation on smartphones. Paper presented 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE; Aalborg, Denmark. https://doi.org/10.1109/mlsp.2018.8516710
Cui Z, Zhou P, Wang X, Zhang Z, Li Y, Li H, Zhang Y (2023) A novel geo-localization method for UAV and satellite images using cross-view consistent attention. Remote Sens 15(19):4667. https://doi.org/10.3390/RS15194667
Cunha RDS (2017) A comunicação dos riscos na preparação para emergências nucleares: um estudo de caso em Angra dos Reis, Rio de Janeiro (PhD thesis). São Paulo: Universidade de São Paulo. https://doi.org/10.11606/T.85.2017.tde-06092017-085924
Dai J, Hao X, Liu S, Ren Z (2022) Research on UAV robust adaptive positioning algorithm based on IMU/GNSS/VO in complex scenes. Sensors 22(8):2832. https://doi.org/10.3390/S22082832
Dantas BNC (2023) Fusão de técnicas de inteligência artificial e visão computacional aplicada à estimação de posição de veículos aéreos com auxílio de imagens satelitais (master’s thesis). São José dos Campos: Instituto Tecnológico de Aeronáutica.
Deilamsalehy H, Havens TC (2016) Sensor fused three-dimensional localization using IMU, camera and LiDAR. Paper presented 2016 IEEE SENSORS. IEEE; Orlando, USA. https://doi.org/10.1109/ICSENS.2016.7808523
Deuser F, Habel K, Oswald N (2023) Sample4Geo: Hard negative sampling for cross-view geo-localisation. Paper presented 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE; Paris, France. https://doi.org/10.1109/ICCV51070.2023.01545
Dong X, Hu G (2016) Time-varying formation control for general linear multi-agent systems with switching directed topologies. Automatica 73:47-55. https://doi.org/10.1016/j.automatica.2016.06.024
Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, et al. (2020) An image is worth 16×16 words: Transformers for image recognition at scale. https://doi.org/10.48550/arxiv.2010.11929
Duan R, Wang J, Jiang C, Yao H, Ren Y, Qian Y (2019) Resource allocation for multi-UAV aided IoT NOMA uplink transmission systems. IEEE Internet Things J 6(4):7025-7037. https://doi.org/10.1109/jiot.2019.2913473
Durgam A, Paheding S, Dhiman V, Devabhaktuni V (2024) Cross-view geo-localization: A survey. IEEE Access 12:192028-192050. https://doi.org/10.1109/access.2024.3507280
Elhashash M, Qin R (2022) Cross-view SLAM solver: Global pose estimation of monocular ground-level video frames for 3d reconstruction using a reference 3d model from satellite images. ISPRS J Photogramm Remote Sens 188:62-74. https://doi.org/10.1016/J.ISPRSJPRS.2022.03.018
Esfahani MA, Wang H, Wu K, Yuan S (2020a) AbolDeepIO: A novel deep inertial odometry network for autonomous vehicles. IEEE Trans Intell Transp Syst 21(5):1941-1950. https://doi.org/10.1109/TITS.2019.2909064
Esfahani MA, Wang H, Wu K, Yuan S (2020b) OriNet: Robust 3-d orientation estimation with a single particular IMU. IEEE Robot Autom Lett 5(2):399-406. https://doi.org/10.1109/LRA.2019.2959507
Farrell J, Farrell JA (2008) Aided navigation. Electronic engineering. New York: McGraw-Hill.
Fervers F, Bullinger S, Bodensteiner C, Arens M, Stiefelhagen R (2023a) C-BEV: Contrastive bird’s eye view training for crossview image retrieval and 3-dof pose estimation. https://arxiv.org/abs/2312.08060
Fervers F, Bullinger S, Bodensteiner C, Arens M, Stiefelhagen R (2023b) Uncertainty-aware vision-based metric cross-view geolocalization. Paper presented 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE; Vancouver, Canada. https://doi.org/10.1109/CVPR52729.2023.02071
Fu S, Hamilton M, Brandt L, Feldman A, Zhang Z, Freeman WT (2024) FeatUp: A model-agnostic framework for features at any resolution. https://arxiv.org/abs/2403.10516
Ge F, Zhang Y, Liu Y, Wang G, Coleman S, Kerr D, Wang L (2024) Multibranch joint representation learning based on information fusion strategy for cross-view geo-localization. IEEE Trans Geosci Remote Sens 62:1-16. https://doi.org/10.1109/TGRS.2024.3378453
Giubilato R, Chiodini S, Pertile M, Debei S (2020) MiniVO: Minimalistic range enhanced monocular system for scale correct pose estimation. IEEE Sensors J 20(20):11874-11886. https://doi.org/10.1109/JSEN.2020.2978334
Goltz GAM, Shiguemori EH, De Campos Velho HF (2016) Position estimation of UAV by image processing with neural networks. Paper presented 2016 10º Congresso Brasileiro de Inteligência Computacional (CBIC). SBIC; Fortaleza, CE. https://doi.org/10.21528/cbic2011-03.6
Gong J, Zhang X, Huang Y, Ren J, Zhang Y (2021) Robust inertial motion tracking through deep sensor fusion across smart earbuds and smartphone. Proc ACM Interact Mob Wearable Ubiquitous Technol 5(2):1-26. https://doi.org/10.1145/3463517
Hegarty CJ, Chatre E (2008) Evolution of the global navigation satellite system (GNSS). Proc IEEE 96(12):1902-1917. https://doi.org/10.1109/jproc.2008.2006090
Hu S, Lee GH (2019) Image-based geo-localization using satellite imagery. Int J Comput Vis 128(5):1205-1219. https://doi.org/10.1007/S11263-019-01186-0
Huang S, Dissanayake G (2007) Convergence and consistency analysis for extended Kalman filter based SLAM. IEEE Trans Robot 23(5):1036-1049. https://doi.org/10.1109/TRO.2007.903811
Huang Y-E, Tsai S, Liu H-Y, Chiang K-W, Tsai M-L, Lee P-L, El-Sheimy N (2023) The development and validation of a tactical grade EGI system for land vehicular navigation applications. Int Arch Photogramm Remote Sens Spatial Inf Sci XLVIII-1/W2-2023:821-828. https://doi.org/10.5194/isprsarchives-xlviii-1-w2-2023-821-2023
Jin R, Zhang G, Hsu L-T, Hu Y (2024) A survey on cooperative positioning using GNSS measurements. IEEE Trans Intell Veh 9(11):7402-7420. https://doi.org/10.1109/tiv.2024.3397879
Joyce KE, Anderson K, Bartolo RE (2021) Of course we fly unmanned – we’re women! Drones 5(1):21. https://doi.org/10.3390/drones5010021
Kalman RE (1960) A new approach to linear filtering and prediction problems. J Basic Eng 82(1):35-45. https://doi.org/10.1115/1.3662552
Kartal S, Kaya YB, Nergiz F, Özbağ E, Yilmaz Y, Dar T (2023) Analysis of GDOP based on GEO satellite. Paper presented 2023 10th International Conference on Recent Advances in Air and Space Technologies (RAST). IEEE; Istanbul, Turkey. https://doi.org/10.1109/rast57548.2023.10197979
Ke J, Xu T, Zeng J, Duan Z (2023) Distributed observer-based tracking of multi-agent systems with bounded input amplitudes and rates. Int J Robust Nonlinear Control 34(4):2781-2805. https://doi.org/10.1002/rnc.7108
Kim W-Y, Seo H-I, Seo D-H (2021) Nine-axis IMU-based extended inertial odometry neural network. Expert Syst Appl 178:115075. https://doi.org/10.1016/J.ESWA.2021.115075
Ko NY, Youn W, Choi IH, Song G, Kim TS (2018) Features of invariant extended Kalman filter applied to unmanned aerial vehicle navigation. Sensors 18(9):2855. https://doi.org/10.3390/s18092855
Kopf J, Cohen MF, Lischinski D, Uyttendaele M (2007) Joint bilateral upsampling. ACM Trans Graph 26(3):96. https://doi.org/10.1145/1276377.1276497
Korsah GA, Stentz A, Dias MB (2013) A comprehensive taxonomy for multi-robot task allocation. Int J Robot Res 32(12):1495-1512. https://doi.org/10.1177/0278364913496484
Li F, Zhao C, Ding G, Gong J, Liu C, Zhao F (2012) A reliable and accurate indoor localization method using phone inertial sensors. Paper presented 2012 ACM Conference on Ubiquitous Computing (Ubicomp’12). ACM; New York, USA. https://doi.org/10.1145/2370216.2370280
Li H, Deuser F, Yin W, Luo X, Walther P, Mai G, Huang W, Werner M (2025) Cross-view geolocalization and disaster mapping with street-view and VHR satellite imagery: A case study of hurricane IAN. ISPRS J Photogramm Remote Sens 220:841-854. https://doi.org/10.1016/j.isprsjprs.2025.01.003
Liu B, Teng Y, Huang Q (2017) GDOP minimum in multi-GNSS positioning. Adv Space Res 60(7):1400-1403. https://doi.org/10.1016/j.asr.2017.06.049
Liu C, Zhao J, Sun N (2022) A review of collaborative air-ground robots research. J Intell Robot Syst 106(3). https://doi.org/10.1007/s10846-022-01756-4
Liu D, Bao W, Zhu X, Fei B, Xiao Z, Men T (2022) Vision-aware air-ground cooperative target localization for UAV and UGV. Aerosp Sci Technol 124:107525. https://doi.org/10.1016/j.ast.2022.107525
Liu L, Li H (2019) Lending orientation to neural networks for cross-view geo-localization. Paper presented 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE; Long Beach, USA. https://doi.org/10.1109/CVPR.2019.00577
Loianno G, Watterson M, Kumar V (2016) Visual inertial odometry for quadrotors on SE(3). Paper presented 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE; Stockholm, Sweden. https://doi.org/10.1109/ICRA.2016.7487292
Lupton T, Sukkarieh S (2009) Efficient integration of inertial observations into visual SLAM without initialization. Paper presented 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE; Saint Louis, EUA. https://doi.org/10.1109/IROS.2009.5354267
Miller ID, Cladera F, Smith T, Taylor CJ, Kumar V (2022) Stronger together: Air-ground robotic collaboration using semantics. IEEE Robot Autom Lett 7(4):9643-9650. https://doi.org/10.1109/lra.2022.3191165
Minetto A, Gurrieri A, Dovis F (2020) A cognitive particle filter for collaborative DGNSS positioning. IEEE Access 8:194765-194779. https://doi.org/10.1109/access.2020.3033626
Mohiuddin A, Tarek T, Zweiri Y, Gan D (2020) A survey of single and multi-UAV aerial manipulation. Unmanned Syst 8(2):119-147. https://doi.org/10.1142/s2301385020500089
Nemra A, Aouf N (2009) Robust airborne 3D visual simultaneous localization and mapping with observability and consistency analysis. J Intell Robot Syst 55(4-5):345-376. https://doi.org/10.1007/s10846-008-9306-6
Or B, Klein I (2022) A hybrid model and learning-based adaptive navigation filter. IEEE Trans Instrum Meas 71:1-11. https://doi.org/10.1109/tim.2022.3197775
Parker LE (2009) Multiple Mobile Robot Teams, Path Planning and Motion Coordination. New York: Springer. https://doi.org/10.1007/978-0-387-30440-3_344
Peng K, Du J, Lu F, Sun Q, Dong Y, Zhou P, Hu M (2019) A hybrid genetic algorithm on routing and scheduling for vehicleassisted multi-drone parcel delivery. IEEE Access 7:49191-49200. https://doi.org/10.1109/access.2019.2910134
Rahman AAA, Jaafar WSWM, Maulud KNA, Noor NM, Mohan M, Cardil A, Silva CA, Che’Ya NN, Naba NI (2019) Applications of drones in emerging economies: A case study of Malaysia. Paper presented 2019 6th International Conference on Space Science and Communication (IconSpace). IEEE; Bahru, Malaysia. https://doi.org/10.1109/ICONSPACE.2019.8905962
Ran H, Sun L, Cheng S, Ma Y, Yan S, Meng S, Shi K, Wen S (2021) A novel cooperative searching architecture for multiunmanned aerial vehicles under restricted communication. Asian J Control 24(2):510-516. https://doi.org/10.1002/asjc.2517
Regmi K, Borji A (2019) Cross-view image synthesis using geometry-guided conditional GANs. Comput Vis Image Underst 187:102788. https://doi.org/10.1016/J.CVIU.2019.07.008
Regmi K, Shah M (2019) Bridging the domain gap for ground-to-aerial image matching. Paper presented 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE; Seoul, Korea. https://doi.org/10.1109/ICCV.2019.00056
Rigatos GG (2012) Nonlinear Kalman filters and particle filters for integrated navigation of unmanned aerial vehicles. Robot Auton Syst 60(7):978-995. https://doi.org/10.1016/j.robot.2012.03.001
Rodrigues R, Tani M (2023) SemGeo: Semantic keywords for cross-view image geo-localization. Paper presented 2023 ICASSP 2023 – 2023 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE; Rhodes Island, Greece. https://doi.org/10.1109/ICASSP49357.2023.10094763
Romero H, Salazar S, Santos O, Lozano R (2013) Visual odometry for autonomous outdoor flight of a quadrotor UAV. Paper presented 2013 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE; Atlanta, USA. https://doi.org/10.1109/icuas.2013.6564748
Roos DR (2018) Aprendizado de máquina aplicado à odometria visual para estimação de posição de veículos aéreos não tripulados (master’s thesis). São Paulo: Universidade Federal de São Paulo. https://doi.org/10.20950/1678-2305/bip.2024.51.e910
Savage PG (2007) Savage, volume 2 of Strapdown Analytics. Maple Plain: Strapdown Associates.
Shen C, Zhang Y, Li Z, Gao F, Shen S (2017) Collaborative air-ground target searching in complex environments. Paper presented 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR). IEEE; Shanghai, China. https://doi.org/10.1109/ssrr.2017.8088168
Shetty A, Gao GX (2019) UAV pose estimation using cross-view geolocalization with satellite imagery. Paper presented 2019 International Conference on Robotics and Automation (ICRA). IEEE; Montreal, Canada. https://doi.org/10.1109/ICRA.2019.8794228
Shi Y, Wu F, Perincherry A, Vora A, Li H (2023) Boosting 3-dof ground-to-satellite camera localization accuracy via geometry-guided cross-view transformer. Paper presented 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE; Paris, France. https://doi.org/10.1109/ICCV51070.2023.01967
Shi Y, Yu X, Liu L, Campbell D, Koniusz P, Li H (2022) Accurate 3-dof camera geo-localization via ground-to-satellite image matching. IEEE Trans Pattern Anal Mach Intell:1-16. https://doi.org/10.1109/TPAMI.2022.3189702
Shi Y, Yu X, Liu L, Zhang T, Li H (2020) Optimal feature transport for cross-view image geo-localization. Proc AAAI Conf Artif Intell 34(07):11990-11997. https://doi.org/10.1609/AAAI.V34I07.6875
Sottile F, Wymeersch H, Caceres MA, Spirito MA (2011) Hybrid GNSS-terrestrial cooperative positioning based on particle filter. Paper presented 2011 IEEE Global Telecommunications Conference -GLOBECOM.IEEE; Houston, USA. https://doi.org/10.1109/glocom.2011.6134002
Sun S, Melamed D, Kitani K (2021) IDOL: Inertial deep orientation-estimation and localization. Proc AAAI Conf Artif Intell 35(7):6128-6137. https://doi.org/10.1609/aaai.v35i7.16763
Tang H, Niu X, Zhang T, Li Y, Liu J (2022) OdoNet: Untethered speed aiding for vehicle navigation without hardware wheeled odometer. IEEE Sens J 22(12):12197-12208. https://doi.org/10.1109/jsen.2022.3169549
Teixeira BOS, Tôrres LAB, Aguirre LA (2010) Filtragem de Kalman com restrições para sistemas não lineares: revisão e novos resultados. Sba: Controle Automação Soc Bras Autom 21(2):127-146. https://doi.org/10.1590/S0103-17592010000200003
Toker A, Zhou Q, Maximov M, Leal-Taixe L (2021) Coming down to earth: Satellite-to-street view synthesis for geolocalization. Paper presented 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE; Nashville, USA. https://doi.org/10.1109/CVPR46437.2021.00642
Torres VAMF, Jaimes BRA, Ribeiro ES, Braga MT, Shiguemori EH, Velho HFC, Torres LCB, Braga AP (2020) Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs. Eng Appl Artif Intell 87:103227. https://doi.org/10.1016/J.ENGAPPAI.2019.08.021
Ulmer MW, Thomas BW (2018) Same-day delivery with heterogeneous fleets of drones and vehicles. Networks 72(4): 475-505. https://doi.org/10.1002/net.21855
Velusamy P, Rajendran S, Mahendran RK, Naseer S, Shafiq M, Choi J-G (2021) Unmanned aerial vehicles (UAV) in precision agriculture: Applications and challenges. Energies 15(1):217. https://doi.org/10.3390/en15010217
Wagstaff B, Peretroukhin V, Kelly J (2020) Robust data-driven zero-velocity detection for foot-mounted inertial navigation. IEEE Sens J 20(2):957-967. https://doi.org/10.1109/jsen.2019.2944412
Wang N (2021) “As it is Africa, it is ok”? Ethical considerations of development use of drones for delivery in Malawi. IEEE Trans Technol Soc 2(1):20-30. https://doi.org/10.1109/TTS.2021.3058669
Wang P, Yang Z, Chen X, Xu H (2023) A Transformer-Based Method for UAV-View Geo-Localization. Cham: Springer. https://doi.org/10.1007/978-3-031-44223-0_27
Wang Q, Luo H, Ye L, Men A, Zhao F, Huang Y, Ou C (2019) Pedestrian heading estimation based on spatial transformer networks and hierarchical LSTM. IEEE Access 7:162309-162322. https://doi.org/10.1109/access.2019.2950728
Wang T, Fan S, Liu D, Sun C (2022) Transformer-guided convolutional neural network for cross-view geolocalization. https://arxiv.org/abs/2204.09967
Wang W, Chen W, Qiu Q, Chen L, Wu B, Lin B, He X, Liu W (2024) CrossFormer++: A versatile vision transformer hinging on cross-scale attention. IEEE Trans Pattern Anal Mach Intell 46(5):3123-3136. https://doi.org/10.1109/TPAMI.2023.3341806
Wang Y, Cheng H, Meng MQ-H (2020) Pedestrian motion tracking by using inertial sensors on the smartphone. Paper presented 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE; Las Vegas, EUA. https://doi.org/10.1109/iros45743.2020.9341173
Wang Y, Kuang J, Li Y, Niu X (2022) Magnetic field-enhanced learning-based inertial odometry for indoor pedestrian. IEEE Trans Instrum Meas 71:1-13. https://doi.org/10.1109/tim.2022.3186358
Wang Y, Kuang J, Niu X, Liu J (2023) LLIO: Lightweight learned inertial odometer. IEEE Internet Things J 10(3):2508-2518. https://doi.org/10.1109/jiot.2022.3214087
Wen W, Bai X, Zhang G, Chen S, Yuan F, Hsu L-T (2020) Multi-agent collaborative GNSS/camera/INS integration aided by inter-ranging for vehicular navigation in urban areas. IEEE Access 8:124323-124338. https://doi.org/10.1109/access.2020.3006210
Williams J (2024) UAV survey mapping of illegal deforestation in Madagascar. Plants People Planet 6(6):1413-1424. https://doi.org/10.1002/ppp3.10533
Wilson D, Zhang X, Sultani W, Wshah S (2023) Image and object geo-localization. Int J Comput Vis 132(4):1350-1392. https://doi.org/10.1007/s11263-023-01942-3
Workman S, Souvenir R, Jacobs N (2015) Wide-area image geolocalization with aerial reference imagery. Paper presented 2015 IEEE International Conference on Computer Vision (ICCV). IEEE; Santiago, Chile. https://doi.org/10.1109/ICCV.2015.451
Wu S, Tang H, Jing X-Y, Qian J, Sebe N, Yan Y, Zhang Q (2022) Cross-view panorama image synthesis with progressive attention GANs. Pattern Recognit 131:108884. https://doi.org/10.1016/J.PATCOG.2022.108884
Xavier NAZ, Shiguemori EH, Maximo MROA (2025a) UAV inertial navigation using deep neural networks in simulated environments. Eng Anal Bound Elem 179:106376. https://doi.org/10.1016/j.enganabound.2025.106376
Xavier NAZ, Shiguemori EH, Maximo MROA, Shah M (2025b) A guided approach for cross-view geolocalization estimation with land cover semantic segmentation. Biomim Intell Robot 5(2):100208. https://doi.org/10.1016/j.birob.2024.100208
Xia Y, Song M, Zhang J, Hu C (2018) An autonomously navigation system for forestry quadrotor within GPS-denied belowcanopy environment. Paper presented 2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC). IEEE; Xiamen, China. https://doi.org/10.1109/GNCC42960.2018.9019136
Xia Z, Booij O, Kooij JFP (2024) Convolutional cross-view pose estimation. IEEE Trans Pattern Anal Mach Intell 46(5): 3813-3831. https://doi.org/10.1109/TPAMI.2023.3346924
Xia Z, Booij O, Manfredi M, Kooij JFP (2022) Visual cross-view metric localization with dense uncertainty estimates. Tel Aviv: Springer. European Conference on Computer Vision (ECCV); p. 90-106. https://doi.org/10.48550/ARXIV.2208.08519
Xie X, Yang T, Ning Y, Zhang F, Zhang Y (2021) A monocular visual odometry method based on virtual-real hybrid map in low-texture outdoor environment. Sensors 21(10):3394. https://doi.org/10.3390/S21103394
Xu H, Wang C, Bo Y, Jiang C, Liu Y, Yang S, Lai W (2022) An aerial and ground multi-agent cooperative location framework in GNSS-challenged environments. Remote Sens 14(19):5055. https://doi.org/10.3390/rs14195055
Xu Y, Wei Y, Wang D, Jiang K, Deng H (2023) Multi-UAV path planning in GPS and communication denial environment. Sensors 23(6):2997. https://doi.org/10.3390/S23062997
Yan H, Shan Q, Furukawa Y (2018) RIDI: Robust IMU Double Integration. Cham: Springer. https://doi.org/10.1007/978-3-030-01261-8_38
Yan Z, Jouandeau N, Cherif AA (2013) A survey and analysis of multi-robot coordination. Int J Adv Robot Syst 10(12). https://doi.org/10.5772/57313
Yang M, Sun X, Jia F, Rushworth A, Dong X, Zhang S, Fang Z, Yang G, Liu B (2022) Sensors and sensor fusion methodologies for indoor odometry: A review. Polymers 14(10):2019. https://doi.org/10.3390/polym14102019
Ye Z, Bao C, Liu X, Bao H, Cui Z, Zhang G (2022) Crossview mapping with graph-based geolocalization on city-scale street maps. Paper presented 2022 International Conference on Robotics and Automation (ICRA). IEEE; Philadelphia, USA. https://doi.org/10.1109/ICRA46639.2022.9811743
Yi S, Jin X, Wang Z, Liu Z, Zorzi M (2025) Data-driven robust UAV position estimation in GPS signal challenged environment. https://arxiv.org/abs/2504.07842
Yu X, Liu B, Lan X, Xiao Z, Lin S, Yan B, Zhou L (2019) AZUPT: Adaptive zero velocity update based on neural networks for pedestrian tracking. Paper presented 2019 IEEE Global Communications Conference (GLOBECOM). IEEE; Waikoloa, USA. https://doi.org/10.1109/globecom38437.2019.9014070
Yuan D, Maire F, Dayoub F (2024) Cross-attention between satellite and ground views for enhanced fine-grained robot geo-localization. Paper presented 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE; Waikoloa, USA. https://doi.org/10.1109/WACV57701.2024.00128
Yue P, Xin J, Huang Y, Zhao J, Zhang C, Chen W, Shan M (2025) UAV autonomous navigation system based on air-ground collaboration in GPS-denied environments. Drones 9(6):442. https://doi.org/10.3390/drones9060442
Zhang L, Gao F, Deng F, Xi L, Chen J (2023) Distributed estimation of a layered architecture for collaborative air-ground target geolocation in outdoor environments. IEEE Trans Ind Electron 70(3): 2822-2832. https://doi.org/10.1109/tie.2022.3165245
Zhang M, Zhang M, Chen Y, Li M (2021) IMU data processing for inertial aided navigation: A recurrent neural network based approach. Paper presented 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE; Xi’an, China. https://doi.org/10.1109/icra48506.2021.9561172
Zhang Q, Zhu Y (2024) Aligning geometric spatial layout in cross-view geo-localization via feature recombination. Proceedings of the AAAI Conference on Artificial Intelligence 38(7):7251-7259. https://doi.org/10.1609/AAAI.V38I7.28554
Zhang X, Li X, Sultani W, Zhou Y, Wshah S (2023) Cross-view geo-localization via learning disentangled geometric layout correspondence. Proceedings of the AAAI Conference on Artificial Intelligence 37(3):3480-3488. https://doi.org/10.1609/AAAI.V37I3.25457
Zhang Y, Shi Y, Wang S, Vora A, Perincherry A, Chen Y, Li H (2024) Increasing SLAM pose accuracy by ground-to-satellite image registration. Paper presented 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE; Yokohama, Japan. https://doi.org/10.1109/ICRA57147.2024.10611079
Zhao J, Zhai Q, Zhao P, Huang R, Cheng H (2023) Co-visual pattern-augmented generative transformer learning for automobile geo-localization. Remote Sens 15(9):2221. https://doi.org/10.3390/RS15092221
Zhou B, Gu Z, Gu F, Wu P, Yang C, Liu X, Li L, Li Y, Li Q (2022) DeepVIP: Deep learning-based vehicle indoor positioning using smartphones. IEEE Trans Veh Technol 71(12):13299-13309. https://doi.org/10.1109/tvt.2022.3199507
Zhou B, Krahenbuhl P (2022) Cross-view transformers for real-time map-view semantic segmentation. Paper presented 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE; New Orleans, USA. https://doi.org/10.1109/CVPR52688.2022.01339
Zhou L, Jiang Y, Jia H, Zhang L, Xu F, Tian Y, Ma Z, Liu X, Guo S, Wu Y, et al. (2024) UAV vision-based crack quantification and visualization of bridges: system design and engineering application. Struct Health Monit 24(2):1083-1100. https://doi.org/10.1177/14759217241251778
Zhu S, Shah M, Chen C (2022) TransGeo: Transformer is all you need for cross-view image geo-localization. Paper presented 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE; New Orleans, USA. https://doi.org/10.1109/CVPR52688.2022.00123
Zhu S, Yang T, Chen C (2021a) Revisiting street-to-aerial view image geo-localization and orientation estimation. Paper presented 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE; Waikoloa, USA. https://doi.org/10.1109/WACV48630.2021.00080
Zhu S, Yang T, Chen C (2021b) VIGOR: Cross-view image geo-localization beyond one-to-one retrieval. Paper presented 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE; Nashville, USA. https://doi.org/10.1109/CVPR46437.2021.00364
Zhu Y, Sun B, Lu X, Jia S (2022) Geographic semantic network for cross-view image geo-localization. IEEE Trans Geosci Remote Sens 60:1-15. https://doi.org/10.1109/TGRS.2021.3121337
Zocca S, Minetto A, Dovis F (2021) Adaptive bayesian state estimation integrating non-stationary DGNSS inter-agent distances. Paper presented 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). IEEE; Helsinki, Finland. https://doi.org/10.1109/vtc2021-spring51267.2021.9448952
Zou Z, Huang T, Ye L, Song K (2020) CNN based adaptive Kalman filter in high-dynamic condition for low cost navigation system on highspeed UAV. Paper presented 2020 5th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS). IEEE; Singapore, Singapore. https://doi.org/10.1109/acirs49895.2020.9162601
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