FM² Path Planner for UAV Applications with Curvature Constraints: A Comparative Analysis with Other Planning...

Area of Science:

• Robotics and Automation
• Aerospace Engineering
• Computational Geometry

Background:

• Path planning is crucial for Unmanned Aerial Vehicle (UAV) operations.
• Existing optimization-based methods often face challenges with computational efficiency and trajectory curvature constraints.
• The need for faster and more adaptable path planning algorithms in UAV applications is critical.

Purpose of the Study:

• To evaluate the Fast Marching Square (FM2) method as a competitive path planner for UAVs.
• To demonstrate the FM2 method's ability to satisfy trajectory curvature constraints efficiently.
• To compare the performance of FM2 against established optimization-based path planning techniques.

Main Methods:

• The study employs the Fast Marching Square (FM2) method for path planning.
• Introduces two key parameters, saturation α and exponent β, for flexible path configuration.
• Conducts a comparative analysis against optimization-based methods like Dubins, Euler-Mumford Elastica, and Reeds-Shepp.

Main Results:

• FM2 directly generates feasible paths that meet curvature restrictions, eliminating the need for post-optimization.
• Achieves significant computational speed improvements, up to 220 times faster than comparative methods.
• Simulation results validate the superiority of FM2 for UAV path planning.

Conclusions:

• The FM2 method presents a highly efficient and flexible solution for UAV path planning.
• Its ability to directly enforce curvature constraints and its speed offer a substantial advantage over traditional optimization techniques.
• FM2 is a promising approach for real-world UAV applications requiring rapid and reliable trajectory generation.