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Spherical Bezier Curve-Based 3D UAV Smooth Path Planning Utilizing an Efficient Improved Exponential-Trigonometric
Yitao Cao1, Kang Chen1, Gang Hu2
1Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China.
Biomimetics (Basel, Switzerland)
|February 26, 2026
Summary
This study introduces an improved optimization algorithm (IETO) for unmanned aerial vehicle (UAV) path planning. The new method generates safer, shorter, and smoother flight paths in complex 3D environments.
Area of Science:
- Robotics
- Artificial Intelligence
- Aerospace Engineering
Background:
- Path planning is crucial for unmanned aerial vehicle (UAV) efficiency but faces limitations in complex environments.
- Traditional algorithms struggle with nonlinear, multimodal, and multiconstraint path planning challenges.
Purpose of the Study:
- To develop an improved optimization algorithm for 3D smooth path planning in UAVs.
- To enhance path safety, efficiency, and adaptability to dynamic threats.
Main Methods:
- A fixed arc length resampling strategy and spherical projection for path smoothing.
- An improved exponential-trigonometric optimization (IETO) algorithm incorporating novel strategies.
- A total cost function considering four cost types for path evaluation.
Main Results:
- IETO demonstrated effectiveness in various optimization problems through diversity, ablation, and benchmark analyses.
- Simulation experiments showed IETO consistently generates shorter, smoother, and safer UAV paths.
- The proposed method adapts well to different terrain features in 3D elevation maps.
Conclusions:
- The improved exponential-trigonometric optimization (IETO) algorithm offers a robust solution for UAV path planning.
- The method enhances flight path safety and efficiency in complex, dynamic environments.
- IETO provides stable and superior path planning performance compared to traditional methods.
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