{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T23:05:45Z","timestamp":1778886345892,"version":"3.51.4"},"reference-count":44,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T00:00:00Z","timestamp":1745539200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62473249"],"award-info":[{"award-number":["62473249"]}]},{"name":"National Natural Science Foundation of China","award":["23ZR1426600"],"award-info":[{"award-number":["23ZR1426600"]}]},{"name":"Natural Science Foundation of Shanghai","award":["62473249"],"award-info":[{"award-number":["62473249"]}]},{"name":"Natural Science Foundation of Shanghai","award":["23ZR1426600"],"award-info":[{"award-number":["23ZR1426600"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Actuators"],"abstract":"<jats:p>This work develops an improved integrated planning and control framework for an unmanned aerial vehicle (UAV) in complex environments with dense obstacles to achieve fast and accurate path planning, trajectory generation, and tracking control. Utilizing the potential function-based rapid-exploration random tree star (P-RRT*), a bidirectional dynamic informed P-RRT* (BDIP-RRT*) algorithm is first introduced to enhance sampling efficiency, facilitating swift path generation. To further optimize the initial path, a greedy algorithm is employed to minimize redundant segments within the generated path. Subsequently, trajectory control points are assigned based on the original path points using an adaptive distance interpolation strategy. A hybrid optimized trajectory generator considering jerk and snap is built to obtain a reference trajectory for the UAV. Moreover, two prescribed-time control laws are designed to ensure fast and accurate UAV position and attitude control. Finally, simulation results are performed to illustrate the effectiveness and superior performances of the developed path planning and control scheme.<\/jats:p>","DOI":"10.3390\/act14050211","type":"journal-article","created":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T08:02:57Z","timestamp":1745568177000},"page":"211","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Fast Dynamic P-RRT*-Based UAV Path Planning and Trajectory Tracking Control Under Dense Obstacles"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6191-2463","authenticated-orcid":false,"given":"Xiangyu","family":"Zhu","sequence":"first","affiliation":[{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufeng","family":"Gao","sequence":"additional","affiliation":[{"name":"Beijing Institute of Spacecraft System Engineering, Beijing 100194, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanyan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Aerospace Science and Technology, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1109\/TII.2021.3080303","article-title":"Incremental twisting fault tolerant control for hypersonic vehicles with partial model knowledge","volume":"18","author":"Han","year":"2022","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"23379","DOI":"10.1109\/JIOT.2022.3206276","article-title":"Adversarial attacks and defenses toward AI-assisted UAV infrastructure inspection","volume":"9","author":"Raja","year":"2022","journal-title":"IEEE Internet Things J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.comcom.2021.01.003","article-title":"Addressing disasters in smart cities through UAVs path planning and 5G communications: A systematic review","volume":"168","author":"Qadir","year":"2021","journal-title":"Comput. Commun."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"113816","DOI":"10.1016\/j.eswa.2020.113816","article-title":"Self-driving cars: A survey","volume":"165","author":"Badue","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106586","DOI":"10.1016\/j.ast.2021.106586","article-title":"Nonlinear optimal attitude control of spacecraft using novel state-dependent coefficient parameterizations","volume":"112","author":"Yao","year":"2021","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"117210","DOI":"10.1016\/j.oceaneng.2024.117210","article-title":"Hybrid path planning method for USV using bidirectional A* and improved DWA considering the manoeuvrability and COLREGs","volume":"298","author":"Xu","year":"2024","journal-title":"Ocean Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"125206","DOI":"10.1016\/j.eswa.2024.125206","article-title":"A hybrid sampling-based RRT* path planning algorithm for autonomous mobile robot navigation","volume":"258","author":"Ganesan","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"106099","DOI":"10.1016\/j.asoc.2020.106099","article-title":"A novel reinforcement learning based grey wolf optimizer algorithm for unmanned aerial vehicles (UAVs) path planning","volume":"89","author":"Qu","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4953","DOI":"10.1109\/TAES.2022.3198925","article-title":"Skeleton extraction and greedy-algorithm-based path planning and its application in UAV trajectory tracking","volume":"58","author":"Chang","year":"2022","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.future.2023.02.004","article-title":"A probability smoothing Bi-RRT path planning algorithm for indoor robot","volume":"143","author":"Ma","year":"2023","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_11","first-page":"100436","article-title":"An improved RRT-connect path planning algorithm of robotic arm for automatic sampling of exhaust emission detection in Industry 4.0","volume":"33","author":"Cheng","year":"2023","journal-title":"J. Ind. Inf. Integr."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Karaman, S., Walter, M.R., Perez, A., Frazzoli, E., and Teller, S. (2011, January 9\u201313). Anytime motion planning using the RRT*. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980479"},{"key":"ref_13","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 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6942976"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1007\/s10514-015-9518-0","article-title":"Potential functions based sampling heuristic for optimal path planning","volume":"40","author":"Qureshi","year":"2015","journal-title":"Auton. Robot."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.eswa.2019.01.032","article-title":"Quick-RRT*: Triangular inequality-based implementation of RRT* with improved initial solution and convergence rate","volume":"123","author":"Jeong","year":"2019","journal-title":"Expert Syst. Appl."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1109\/TIV.2022.3150748","article-title":"GMR-RRT*: Sampling-based path planning using Gaussian mixture regression","volume":"7","author":"Wang","year":"2022","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.robot.2018.06.013","article-title":"Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments","volume":"108","author":"Tahir","year":"2018","journal-title":"Robot. Auton. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"113425","DOI":"10.1016\/j.eswa.2020.113425","article-title":"PQ-RRT*: An improved path planning algorithm for mobile robots","volume":"152","author":"Li","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s10514-022-10044-x","article-title":"AEB-RRT*: An adaptive extension bidirectional RRT* algorithm","volume":"46","author":"Wang","year":"2022","journal-title":"Auton. Robot."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Tang, L., Wang, H., Li, P., and Wang, Y. (2019, January 6\u20138). Real-time trajectory generation for quadrotors using B-spline based non-uniform kinodynamic search. Proceedings of the 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO), Dali, China.","DOI":"10.1109\/ROBIO49542.2019.8961485"},{"key":"ref_21","unstructured":"Inaba, M., and Corke, P. (2016). Polynomial trajectory planning for aggressive quadrotor flight in dense indoor environments. Robotics Research, Proceedings of the 16th International Symposium ISRR, Singapore, 16\u201319 December 2013, Springer International Publishing."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gao, F., and Shen, S. (2016, January 23\u201327). Online quadrotor trajectory generation and autonomous navigation on point clouds. Proceedings of the 2016\nIEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Lausanne, Switzerland.","DOI":"10.1109\/SSRR.2016.7784290"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3461","DOI":"10.1109\/TITS.2022.3224785","article-title":"Trajectory and velocity planning method of emergency rescue vehicle based on segmented three-dimensional quartic bezier curve","volume":"24","author":"Chen","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3529","DOI":"10.1109\/LRA.2019.2927938","article-title":"Robust and efficient quadrotor trajectory generation for fast autonomous flight","volume":"4","author":"Zhou","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"100543","DOI":"10.1016\/j.paerosci.2019.05.003","article-title":"A review of optimization techniques in spacecraft flight trajectory design","volume":"109","author":"Chai","year":"2019","journal-title":"Prog. Aerosp. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1109\/TRO.2021.3100142","article-title":"FASTER: Fast and safe trajectory planner for navigation in unknown environments","volume":"38","author":"Tordesillas","year":"2022","journal-title":"IEEE Trans. Robot."},{"key":"ref_27","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 2011 IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980409"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2406","DOI":"10.1109\/TAES.2019.2949384","article-title":"Trajectory optimization for high-altitude long-endurance UAV maritime radar surveillance","volume":"56","author":"Brown","year":"2020","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.isatra.2018.09.020","article-title":"Dynamic path planning and trajectory tracking using MPC for satellite with collision avoidance","volume":"84","author":"Hu","year":"2019","journal-title":"ISA Trans."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"107014","DOI":"10.1016\/j.ast.2021.107014","article-title":"Integration of path planning, trajectory generation and trajectory tracking control for aircraft mission autonomy","volume":"118","author":"Woo","year":"2021","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/TII.2011.2123906","article-title":"Neural network assisted computationally simple PI\u03bbD\u03bc control of a quadrotor UAV","volume":"7","author":"Efe","year":"2011","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1016\/j.ast.2018.06.017","article-title":"A novel control scheme for quadrotor UAV based upon active disturbance rejection control","volume":"79","author":"Zhang","year":"2018","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"105526","DOI":"10.1016\/j.ast.2019.105526","article-title":"Backstepping and dynamic inversion combined controller for auto-landing of fixed wing UAVs","volume":"96","author":"Lungu","year":"2020","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1109\/TAES.2021.3101562","article-title":"Appointed fixed time observer-based sliding mode control for a quadrotor UAV under external disturbances","volume":"58","author":"Li","year":"2022","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2743","DOI":"10.1109\/TMECH.2020.2990582","article-title":"Backstepping sliding-mode and cascade active disturbance rejection control for a quadrotor UAV","volume":"25","author":"Xu","year":"2020","journal-title":"IEEE-ASME Trans. Mechatron."},{"key":"ref_36","first-page":"7281","article-title":"Distributed fixed-time leader-following formation control for multiquadrotors with prescribed performance and collision avoidance","volume":"59","author":"Li","year":"2023","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Li, B., Liu, H., Ahn, C.K., Wang, C., and Zhu, X. (IEEE\/ASME Trans. Mechatron., 2024). Fixed-time tracking control of wheel mobile robot in slipping and skidding conditions, IEEE\/ASME Trans. Mechatron., early access.","DOI":"10.1109\/TMECH.2024.3401069"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"108322","DOI":"10.1016\/j.ast.2023.108322","article-title":"Prescribed-time extended state observer and prescribed performance control of quadrotor UAVs against actuator faults","volume":"138","author":"Gong","year":"2023","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.automatica.2017.06.008","article-title":"Time-varying feedback for regulation of normal-form nonlinear systems in prescribed finite time","volume":"83","author":"Song","year":"2017","journal-title":"Automatica"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2922","DOI":"10.1109\/TII.2017.2682900","article-title":"A new disturbance attenuation control scheme for quadrotor unmanned aerial vehicles","volume":"13","author":"Xiao","year":"2017","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_41","unstructured":"Jordan, M., and Perez, A. (2013). Optimal Bidirectional Rapidly-Exploring Random Trees, Massachusetts Institute of Technology. Technical Report MIT-CSAIL-TR-2013-021."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2332","DOI":"10.2514\/1.G006645","article-title":"Global incremental flight control for agile maneuvering of a tailsitter flying wing","volume":"45","author":"Tal","year":"2022","journal-title":"J. Guid. Control Dyn."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1109\/TCST.2020.3001117","article-title":"Accurate tracking of aggressive quadrotor trajectories using incremental nonlinear dynamic inversion and differential flatness","volume":"29","author":"Tal","year":"2021","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"108833","DOI":"10.1016\/j.ast.2023.108803","article-title":"Optimized intelligent tracking control for a quadrotor unmanned aerial vehicle with actuator failures","volume":"144","author":"Li","year":"2024","journal-title":"Aerosp. Sci. Technol."}],"container-title":["Actuators"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-0825\/14\/5\/211\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:21:27Z","timestamp":1760030487000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-0825\/14\/5\/211"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,25]]},"references-count":44,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,5]]}},"alternative-id":["act14050211"],"URL":"https:\/\/doi.org\/10.3390\/act14050211","relation":{},"ISSN":["2076-0825"],"issn-type":[{"value":"2076-0825","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,25]]}}}