{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T19:20:38Z","timestamp":1780428038198,"version":"3.54.1"},"reference-count":35,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T00:00:00Z","timestamp":1632268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFD1100203"],"award-info":[{"award-number":["2020YFD1100203"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The ability of an autonomous Unmanned Aerial Vehicle (UAV) in an unknown environment is a prerequisite for its execution of complex tasks and is the main research direction in related fields. The autonomous navigation of UAVs in unknown environments requires solving the problem of autonomous exploration of the surrounding environment and path planning, which determines whether the drones can complete mission-based flights safely and efficiently. Existing UAV autonomous flight systems hardly perform well in terms of efficient exploration and flight trajectory quality. This paper establishes an integrated solution for autonomous exploration and path planning. In terms of autonomous exploration, frontier-based and sampling-based exploration strategies are integrated to achieve fast and effective exploration performance. In the study of path planning in complex environments, an advanced Rapidly Exploring Random Tree (RRT) algorithm combining the adaptive weights and dynamic step size is proposed, which effectively solves the problem of balancing flight time and trajectory quality. Then, this paper uses the Hermite difference polynomial to optimization the trajectory generated by the RRT algorithm. We named proposed UAV autonomous flight system as Frontier and Sampling-based Exploration and Advanced RRT Planner system (FSEPlanner). Simulation performs in both apartment and maze environment, and results show that the proposed FSEPlanner algorithm achieves greatly improved time consumption and path distances, and the smoothed path is more in line with the actual flight needs of a UAV.<\/jats:p>","DOI":"10.3390\/ijgi10100631","type":"journal-article","created":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T22:50:48Z","timestamp":1632351048000},"page":"631","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Efficient and High Path Quality Autonomous Exploration and Trajectory Planning of UAV in an Unknown Environment"],"prefix":"10.3390","volume":"10","author":[{"given":"Leyang","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinbiao","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Civil Aviation, Northwestern Polytechnical University, Xi\u2019an 710068, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenbao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Civil Aviation, Northwestern Polytechnical University, Xi\u2019an 710068, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shen, S., Mulgaonkar, Y., Michael, N., and Kumar, V. (June, January 31). Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft MAV. Proceedings of the 2014 IEEE International Conference on Robotics and Automation, Hong Kong, China.","DOI":"10.1109\/ICRA.2014.6907588"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1109\/LRA.2016.2633290","article-title":"Estimation, control, and planning for aggressive flight with a small quadrotor with a single camera and IMU","volume":"2","author":"Loianno","year":"2016","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1688","DOI":"10.1109\/LRA.2017.2663526","article-title":"Planning dynamically feasible trajectories for quadrotors using safe flight corridors in 3-d complex environments","volume":"2","author":"Liu","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Papachristos, C., Kamel, M., Popovi\u0107, M., Khattak, S., Bircher, A., Oleynikova, H., and Siegwart, R. (2019). Autonomous exploration and inspection path planning for aerial robots using the robot operating system. Robot Operating System, Springer.","DOI":"10.1007\/978-3-319-91590-6_3"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Tang, S., and Kumar, V. (2018). A complete algorithm for generating safe trajectories for multi-robot teams. Robotics Research, Springer.","DOI":"10.1007\/978-3-319-60916-4_34"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/MRA.2013.2253172","article-title":"Obtaining liftoff indoors: Autonomous navigation in confined indoor environments","volume":"20","author":"Shen","year":"2013","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_7","unstructured":"Stumberg, L., Usenko, V., Engel, J., St\u00fcckler, J., and Cremers, D. (2017, January 6\u20138). From monocular SLAM to autonomous drone exploration. Proceedings of the 2017 European Conference on Mobile Robots, Paris, France."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Shen, S., Michael, N., and Kumar, V. (2012, January 14\u201318). Autonomous indoor 3D exploration with a micro-aerial vehicle. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6225146"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Fraundorfer, F., Heng, L., Honegger, D., Lee, G.H., Meier, L., Tanskanen, P., and Pollefeys, M. (2012, January 7\u201312). Vision-based autonomous mapping and exploration using a quadrotor MAV. Proceedings of the 2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Vilamoura-Algarve, Portugal.","DOI":"10.1109\/IROS.2012.6385934"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Song, S., and Jo, S. (2018, January 21\u201325). Surface-based exploration for autonomous 3D modelling. Proceedings of the IEEE International Conference on Robotics and Automation, Brisbane, QLD, Australia.","DOI":"10.1109\/ICRA.2018.8460862"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Dharmadhikari, M., Dang, T., Solanka, L., Loje, J., Nguyen, H., Khedekar, N., and Alexis, K. (August, January 31). Motion primitives-based path planning for fast and agile exploration using aerial robots. Proceedings of the 2020 IEEE International Conference on Robotics and Automation, Paris, France.","DOI":"10.1109\/ICRA40945.2020.9196964"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1260\/175682909790291492","article-title":"Autonomous flight in unknown indoor environments","volume":"1","author":"Bachrach","year":"2009","journal-title":"Int. J. Micro Air Veh."},{"key":"ref_13","unstructured":"Yamauchi, B. (1997, January 10\u201311). A frontier-based approach for autonomous exploration. Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automationm, Monterey, CA, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1002\/rob.21520","article-title":"Autonomous Visual Mapping and Exploration with a Micro Aerial Vehicle","volume":"31","author":"Heng","year":"2014","journal-title":"J. Field Robot."},{"key":"ref_15","unstructured":"Connolly, C. (1985, January 25\u201328). The determination of next best views. Proceedings of the IEEE International Conference on Robotics and Automation, St. Louis, MO, USA."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Papachristos, C., Khattak, S., and Alexis, K. (June, January 29). Uncertainty-aware receding horizon exploration and mapping using aerial robots. Proceedings of the 2017 IEEE International Conference on Robotics and Automation, Singapore.","DOI":"10.1109\/ICRA.2017.7989531"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1177\/0278364902021010834","article-title":"Navigation strategies for exploring indoor environments","volume":"21","author":"Latombe","year":"2002","journal-title":"Int. J. Robot. Res."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Witting, C., Fehr, M., B\u00e4hnemann, R., Oleynikova, H., and Siegwart, R. (2018, January 1\u20135). History-aware autonomous exploration in confined environments using mavs. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Madrid, Spain.","DOI":"10.1109\/IROS.2018.8594502"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bircher, A., Kamel, M., Alexis, K., Oleynikova, H., and Siegwart, R. (2016, January 16\u201321). Receding horizon \u201dnext-best-view\u201d planner for 3d exploration. Proceedings of the 2016 IEEE International Conference on Robotics and Automation, Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487281"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Dashkevich, A., Rosokha, S., and Vorontsova, D. (2020, January 5\u201310). Simulation Tool for the Drone Trajectory Planning Based on Genetic Algorithm Approach. Proceedings of the 2020 IEEE KhPI Week on Advanced Technology, Kharkiv, Ukraine.","DOI":"10.1109\/KhPIWeek51551.2020.9250173"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ge, J., Liu, L., Dong, X., and Tian, W. (2020, January 9\u201315). Trajectory Planning of Fixed-wing UAV Using Kinodynamic RRT* Algorithm. Proceedings of the 2020 10th International Conference on Information Science and Technology (ICIST), London, UK.","DOI":"10.1109\/ICIST49303.2020.9202213"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kim, S., Sreenath, K., Bhattacharya, S., and Kumar, V. (2012, January 10\u201313). Optimal trajectory generation under homology class constraints. Proceedings of the 2012 IEEE 51st IEEE Conference on Decision and Control, Maui, HI, USA.","DOI":"10.1109\/CDC.2012.6425970"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TSSC.1968.300136","article-title":"A Formal Basis for the Heuristic Determination of Minimum Cost Paths","volume":"4","author":"Hart","year":"1968","journal-title":"IEEE Trans. Syst. Sci. Cybern."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/rob.20109","article-title":"Using interpolation to improve path planning: The Field D* algorithm","volume":"23","author":"Ferguson","year":"2006","journal-title":"J. Field Robot."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ferguson, D., and Anthony, S. (2007). Field D*: An interpolation-based path planner and replanner. Robotics Research, Springer.","DOI":"10.1007\/978-3-540-48113-3_22"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1109\/70.508439","article-title":"Probabilistic roadmaps for path planning in high-dimensional configuration spaces","volume":"12","author":"Kavraki","year":"1996","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1177\/02783640122067453","article-title":"Randomized kinodynamic planning","volume":"20","author":"LaValle","year":"2001","journal-title":"Int. J. Robot. Res."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Geraerts, R., and Mark, H.O. (2004). A comparative study of probabilistic roadmap planners. Algorithmic Foundations of Robotics V, Springer.","DOI":"10.1007\/978-3-540-45058-0_4"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Karaman, S., and Frazzoli, E. (2010). Incremental sampling-based algorithms for optimal motion planning. Robotics Science and Systems.","DOI":"10.15607\/RSS.2010.VI.034"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Adiyatov, O., and Varol, H.A. (2013). Rapidly-exploring random tree based memory efficient motion planning. Mechatronics and Automation (ICMA), Nazarbayev University.","DOI":"10.1109\/ICMA.2013.6617944"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gammell, J.D., Srinivasa, S.S., and Barfoot, T.D. (2014, January 14\u201318). Informed RRT*: Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristic. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6942976"},{"key":"ref_32","unstructured":"Kuffner, J.J., and LaValle, S.M. (2000, January 24\u201328). RRT-connect: An efficient approach to single-query path planning. Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, CA, USA."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1109\/TCST.2008.2012116","article-title":"Real-time motion planning with applications to autonomous urban driving","volume":"17","author":"Kuwata","year":"2009","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1109\/LRA.2018.2792537","article-title":"Efficient octree-based volumetric SLAM supporting signed-distance and occupancy mapping","volume":"3","author":"Vespa","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1080\/00029890.1960.11989446","article-title":"A generalization of Hermite\u2019s interpolation formula","volume":"67","author":"Spitzbart","year":"1960","journal-title":"Am. Math. Mon."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/10\/631\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:03:24Z","timestamp":1760166204000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/10\/631"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,22]]},"references-count":35,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["ijgi10100631"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10100631","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,22]]}}}