{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T05:02:14Z","timestamp":1784869334556,"version":"3.55.0"},"reference-count":47,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T00:00:00Z","timestamp":1784678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jiangsu Autonomous Driving Technology Innovation and Application Engineering Research Center","award":["ZK25-06-09"],"award-info":[{"award-number":["ZK25-06-09"]}]},{"DOI":"10.13039\/501100013088","name":"Qing Lan Project","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100013088","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Offline action prediction does not by itself guarantee reliable closed-loop flight for unmanned aerial vehicle (UAV) vision-language-action (VLA) models. We study a controlled AirSim Blocks waypoint task using 100 expert episodes and 3385 RGB-D, instruction, state, and action records. Checkpoints are selected only on val-seen data, after which val-unseen is evaluated once. A 132,840-parameter policy reaches 0.9278\u00b10.0019 final-test action accuracy across three training seeds, yet raw VLA control fails in closed loop. We therefore embed its action proposals in progress-aware hybrid execution with explicit recovery and near-goal precision. The strongest checkpoint reaches 59\/60 goals, but crossing three independently trained checkpoints with three target seeds yields a more conservative 147\/180 successes (81.7%) with zero recorded collisions and marked checkpoint sensitivity. Substantial overrides and fallback-tagged steps further show that the reported closed-loop outcomes are properties of the hybrid system, not of the learned policy alone. These findings are restricted to the controlled AirSim Blocks benchmark and do not demonstrate real-UAV deployment, sim-to-real transfer, or field robustness.<\/jats:p>","DOI":"10.3390\/s26144655","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T01:01:28Z","timestamp":1784768488000},"page":"4655","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Lightweight Vision-Language-Action Policy with Progress-Aware Hybrid Execution for UAV Waypoint Navigation in AirSim"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7962-6668","authenticated-orcid":false,"given":"Yiqing","family":"Xu","sequence":"first","affiliation":[{"name":"School of Computer and Software\/School of Artificial Intelligence, Nanjing University of Industry Technology, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3835-6075","authenticated-orcid":false,"given":"Haifeng","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology & Artificial Intelligence, Nanjing Forestry University, Nanjing 210037, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1051-1993","authenticated-orcid":false,"given":"Yujin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Transportation Engineering, Nanjing University of Industry Technology, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji\u2019An","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Computer and Software\/School of Artificial Intelligence, Nanjing University of Industry Technology, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8733-194X","authenticated-orcid":false,"given":"Zidong","family":"Han","sequence":"additional","affiliation":[{"name":"School of Aeronautic Engineering, Nanjing University of Industry Technology, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Anderson, P., Wu, Q., Teney, D., Bruce, J., Johnson, M., Sunderhauf, N., Reid, I., Gould, S., and van den Hengel, A. (2018, January 18\u201322). Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00387"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Liu, S., Zhang, H., Qi, Y., Wang, P., Zhang, Y., and Wu, Q. (2023, January 2\u20136). AerialVLN: Vision-and-Language Navigation for UAVs. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France.","DOI":"10.1109\/ICCV51070.2023.01411"},{"key":"ref_3","first-page":"2165","article-title":"RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control","volume":"Volume 229","author":"Zitkovich","year":"2023","journal-title":"Proceedings of the 7th Conference on Robot Learning"},{"key":"ref_4","first-page":"2679","article-title":"OpenVLA: An Open-Source Vision-Language-Action Model","volume":"Volume 270","author":"Kim","year":"2025","journal-title":"Proceedings of the 8th Conference on Robot Learning, Munich, Germany, 6\u20139 November 2024"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Shah, S., Dey, D., Lovett, C., and Kapoor, A. (2018). AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles. Proceedings of the Field and Service Robotics, Springer.","DOI":"10.1007\/978-3-319-67361-5_40"},{"key":"ref_6","unstructured":"Fried, D., Hu, R., Cirik, V., Rohrbach, A., Andreas, J., Morency, L.P., Berg-Kirkpatrick, T., Saenko, K., Klein, D., and Darrell, T. (2018, January 3\u20138). Speaker-Follower Models for Vision-and-Language Navigation. Proceedings of the Advances in Neural Information Processing Systems, Montr\u00e9al, QC, Canada."},{"key":"ref_7","unstructured":"Ma, C.Y., Lu, J., Wu, Z., AlRegib, G., Kira, Z., Socher, R., and Xiong, C. (2019, January 6\u20139). Self-Monitoring Navigation Agent via Auxiliary Progress Estimation. Proceedings of the International Conference on Learning Representations, New Orleans, LA, USA."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hao, W., Li, C., Li, X., Carin, L., and Gao, J. (2020, January 13\u201319). Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.01315"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Hong, Y., Wu, Q., Qi, Y., Rodriguez-Opazo, C., and Gould, S. (2021, January 20\u201325). VLN BERT: A Recurrent Vision-and-Language BERT for Navigation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA.","DOI":"10.1109\/CVPR46437.2021.00169"},{"key":"ref_10","unstructured":"Chen, S., Guhur, P.L., Schmid, C., and Laptev, I. (2021, January 6\u201314). History Aware Multimodal Transformer for Vision-and-Language Navigation. Proceedings of the Advances in Neural Information Processing Systems, Virtual."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chen, S., Guhur, P.L., Tapaswi, M., Schmid, C., and Laptev, I. (2022, January 18\u201324). Think Global, Act Local: Dual-Scale Graph Transformer for Vision-and-Language Navigation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, USA.","DOI":"10.1109\/CVPR52688.2022.01604"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chen, H., Suhr, A., Misra, D., Snavely, N., and Artzi, Y. (2019, January 15\u201320). Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.01282"},{"key":"ref_13","unstructured":"Mirowski, P., Grimes, M.K., Malinowski, M., Hermann, K.M., Anderson, K., Teplyashin, D., Simonyan, K., Kavukcuoglu, K., Zisserman, A., and Hadsell, R. (2019). The StreetLearn Environment and Dataset. arXiv."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lee, J., Miyanishi, T., Kurita, S., Sakamoto, K., Azuma, D., Matsuo, Y., and Inoue, N. (2025, January 19\u201320). CityNav: A Large-Scale Dataset for Real-World Aerial Navigation. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Honolulu, HI, USA.","DOI":"10.1109\/ICCV51701.2025.00559"},{"key":"ref_15","unstructured":"Ning, Y., Zhao, G., Qin, Y., Liu, S., Liu, Y., Lin, L., and Li, G. (2026, January 3\u20137). LookasideVLN: Direction-Aware Aerial Vision-and-Language Navigation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Denver, CO, USA."},{"key":"ref_16","unstructured":"Fan, C., Pan, C., Liu, Z., Liu, N., and Qin, J. (2026, January 3\u20137). HTNav: A Hybrid Navigation Framework with Tiered Structure for Urban Aerial Vision-and-Language Navigation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Denver, CO, USA."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Dabis, J., Finn, C., Gopalakrishnan, K., Hausman, K., Herzog, A., and Hsu, J. (2023, January 10\u201314). RT-1: Robotics Transformer for Real-World Control at Scale. Proceedings of the Robotics: Science and Systems 2023, Daegu, Republic of Korea.","DOI":"10.15607\/RSS.2023.XIX.025"},{"key":"ref_18","unstructured":"Open X-Embodiment Collaboration, O\u2019Neill, A., Rehman, A., Gupta, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., and Gupta, A. (2024, January 13\u201317). Open X-Embodiment: Robotic Learning Datasets and RT-X Models. Proceedings of the IEEE International Conference on Robotics and Automation, Yokohama, Japan."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ghosh, D., Walke, H., Pertsch, K., Black, K., Mees, O., Dasari, S., Hejna, J., Kreiman, T., Xu, C., and Luo, J. (2024, January 15\u201319). Octo: An Open-Source Generalist Robot Policy. Proceedings of the Robotics: Science and Systems 2024, Delft, The Netherlands.","DOI":"10.15607\/RSS.2024.XX.090"},{"key":"ref_20","first-page":"8469","article-title":"PaLM-E: An Embodied Multimodal Language Model","volume":"Volume 202","author":"Driess","year":"2023","journal-title":"Proceedings of the 40th International Conference on Machine Learning, 2023"},{"key":"ref_21","first-page":"287","article-title":"Do As I Can, Not As I Say: Grounding Language in Robotic Affordances","volume":"Volume 205","author":"Ahn","year":"2023","journal-title":"Proceedings of the 6th Conference on Robot Learning"},{"key":"ref_22","first-page":"991","article-title":"BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning","volume":"Volume 164","author":"Jang","year":"2022","journal-title":"Proceedings of the 5th Conference on Robot Learning"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1684","DOI":"10.1177\/02783649241273668","article-title":"Diffusion Policy: Visuomotor Policy Learning via Action Diffusion","volume":"44","author":"Chi","year":"2025","journal-title":"Int. J. Robot. Res."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zhao, T.Z., Kumar, V., Levine, S., and Finn, C. (2023, January 10\u201314). Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware. Proceedings of the Robotics: Science and Systems 2023, Daegu, Republic of Korea.","DOI":"10.15607\/RSS.2023.XIX.016"},{"key":"ref_25","unstructured":"Wu, Y., Zhu, M., Li, X., Du, Y., Fan, Y., Li, W., Han, Z., Zhou, X., and Gao, F. (2025). VLA-AN: An Efficient and Onboard Vision-Language-Action Framework for Aerial Navigation in Complex Environments. arXiv."},{"key":"ref_26","unstructured":"Xu, P., Deng, Z., Deng, J., Gu, Z., and Wan, S. (2026). AerialVLA: A Vision-Language-Action Model for UAV Navigation via Minimalist End-to-End Control. arXiv."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Ma, C.Y., Wu, Z., AlRegib, G., Xiong, C., and Kira, Z. (2019, January 15\u201320). The Regretful Agent: Heuristic-Aided Navigation Through Progress Estimation. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00689"},{"key":"ref_28","unstructured":"Ross, S., Gordon, G.J., and Bagnell, J.A. (2011, January 11\u201313). A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, Fort Lauderdale, FL, USA."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3861","DOI":"10.1109\/TAC.2016.2638961","article-title":"Control Barrier Function Based Quadratic Programs for Safety Critical Systems","volume":"62","author":"Ames","year":"2017","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1109\/100.580977","article-title":"The Dynamic Window Approach to Collision Avoidance","volume":"4","author":"Fox","year":"1997","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Mellinger, D., and Kumar, V. (2011, January 9\u201313). Minimum Snap Trajectory Generation and Control for Quadrotors. Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980409"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Meier, L., Honegger, D., and Pollefeys, M. (2015, January 26\u201330). PX4: A Node-Based Multithreaded Open Source Robotics Framework for Deeply Embedded Platforms. Proceedings of the IEEE International Conference on Robotics and Automation, Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7140074"},{"key":"ref_33","unstructured":"Song, Y., Naji, S., Kaufmann, E., Loquercio, A., and Scaramuzza, D. (2020, January 16\u201318). Flightmare: A Flexible Quadrotor Simulator. Proceedings of the 4th Conference on Robot Learning, Virtual."},{"key":"ref_34","unstructured":"Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., and Koltun, V. (2017, January 13\u201315). CARLA: An Open Urban Driving Simulator. Proceedings of the 1st Annual Conference on Robot Learning, Mountain View, CA, USA."},{"key":"ref_35","unstructured":"Savva, M., Kadian, A., Maksymets, O., Zhao, Y., Wijmans, E., Jain, B., Straub, J., Liu, J., Koltun, V., and Malik, J. (November, January 27). Habitat: A Platform for Embodied AI Research. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Seoul, Republic of Korea."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Xia, F., Zamir, A.R., He, Z., Sax, A., Malik, J., and Savarese, S. (2018, January 18\u201322). Gibson Env: Real-World Perception for Embodied Agents. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00945"},{"key":"ref_37","unstructured":"Kolve, E., Mottaghi, R., Han, W., VanderBilt, E., Weihs, L., Herrasti, A., Deitke, M., Ehsani, K., Gordon, D., and Zhu, Y. (2017). AI2-THOR: An Interactive 3D Environment for Visual AI. arXiv."},{"key":"ref_38","unstructured":"Howard, A.G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., and Adam, H. (2017). MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. arXiv."},{"key":"ref_39","unstructured":"Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., and Keutzer, K. (2017, January 24\u201326). SqueezeNet: AlexNet-Level Accuracy with 50\u00d7 Fewer Parameters and <0.5 MB Model Size. Proceedings of the International Conference on Learning Representations, Toulon, France."},{"key":"ref_40","unstructured":"Tan, M., and Le, Q.V. (2019, January 9\u201315). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA."},{"key":"ref_41","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., and Polosukhin, I. (2017, January 4\u20139). Attention Is All You Need. Proceedings of the Advances in Neural Information Processing Systems, Long Beach, CA, USA."},{"key":"ref_42","unstructured":"Devlin, J., Chang, M.W., Lee, K., and Toutanova, K. (2019, January 2\u20137). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics, Minneapolis, MN, USA."},{"key":"ref_43","unstructured":"Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., and Clark, J. (2021, January 18\u201324). Learning Transferable Visual Models from Natural Language Supervision. Proceedings of the 38th International Conference on Machine Learning, Virtual."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10514-012-9281-4","article-title":"PIXHAWK: A Micro Aerial Vehicle Design for Autonomous Flight using Onboard Computer Vision","volume":"33","author":"Meier","year":"2012","journal-title":"Auton. Robot."},{"key":"ref_45","unstructured":"Loshchilov, I., and Hutter, F. (2019, January 6\u20139). Decoupled Weight Decay Regularization. Proceedings of the International Conference on Learning Representations, New Orleans, LA, USA."},{"key":"ref_46","unstructured":"Ba, J.L., Kiros, J.R., and Hinton, G.E. (2016). Layer Normalization. arXiv."},{"key":"ref_47","unstructured":"Kingma, D.P., and Ba, J. (2015, January 7\u20139). Adam: A Method for Stochastic Optimization. Proceedings of the International Conference on Learning Representations, San Diego, CA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/14\/4655\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T04:23:53Z","timestamp":1784867033000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/14\/4655"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,22]]},"references-count":47,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["s26144655"],"URL":"https:\/\/doi.org\/10.3390\/s26144655","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,22]]}}}