# An Efficient Trajectory Planning Method for High-Speed Interception of Invasive Drones
## 7 Conclusions  
This research has yielded notable advancements in the trajectory planning for the high-speed flight of quadrotor drones, as well as the interception of unauthorized drones:  
1. This article proposes an efficient method for planning the high-speed flight trajectory of quadcopter unmanned aerial vehicles. Based on linearized approximation of the air resistance model, it effectively compensates for the error between the rigid body model with six degrees of freedom and the real high-speed flight conditions, ensuring the high-speed flight effect of the unmanned aerial vehicle under real physical conditions.
2. By linearizing the dynamic model of resistance and utilizing the optimal control Pontryagin principle, the closed form solution of the optimal trajectory motion primitive was obtained, achieving an efficient solution for the optimal trajectory of quadcopter high-speed flight.
3. The effectiveness of the proposed method was verified through physical simulation, and compared to existing methods, the planning results under high-speed flight conditions have a higher accuracy than the actual simulation flight results.
4. The method proposed in this article can provide an accurate estimation of task time and energy consumption indicators for UAV flight tasks in complex high-speed scenarios, and can quickly evaluate UAV performance indicators in specific task scenarios.
5. The method proposed in this article provides a new approach for trajectory planning of quadcopter drones under high-speed flight conditions, which can be widely applied in complex high-speed flight mission scenarios of drones.  
Nevertheless, this study is not without its limitations and potential for future enhancements:  
1. In real-world applications, drones may be required to work in tandem with other drones to accomplish tasks. Future investigations could explore multi-drone collaborative task scenarios, taking into account factors such as communication, cooperation, and task allocation among the drones to enhance overall task execution efficiency.
2. In real-world scenarios, drones may be required to execute tasks involving larger and more variable targets. Future investigations could delve deeper into intricate situations with extensive targets to ascertain the algorithm's robustness and efficacy.
3. While this paper primarily addresses the efficiency of interception tasks in trajectory planning, it offers limited discussion on the specifics of sensor and interceptor configurations. Future research could explore the integration of a broader range of sensors and mechanisms into different task contexts using the methodologies presented herein, thereby broadening the system's versatility across various scenarios.  
Figure 16: The presentation of our method simulation results in a 3D view.  
**Author Contributions:** Conceptualization, Y.Z. and J.Z.; methodology, Y.Z. and J.Z.; software, Y.Z. and J.Z.; validation, X.G. and Z.H.; formal analysis, Y.Z. and J.Z.; investigation, Y.Z.; resources, X.G. and Z.H.; data curation, Y.Z.; writing\(-\)original draft preparation, Y.Z. and J.Z.; writing\(-\)review and editing, X.G. and Z.H.; visualization, Y.Z.; supervision, X.G. and Z.H.; project administration, Z.H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.