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https://github.com/byuflowlab/uav-path-optimization

2D path-planning algorithm which uses a receding horizon approach and quadratic Bezier curves.

https://github.com/byuflowlab/uav-path-optimization

Science Score: 26.0%

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    Found 1 DOI reference(s) in README
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    Low similarity (7.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

2D path-planning algorithm which uses a receding horizon approach and quadratic Bezier curves.

Basic Info
  • Host: GitHub
  • Owner: byuflowlab
  • Language: MATLAB
  • Default Branch: master
  • Homepage:
  • Size: 4.33 MB
Statistics
  • Stars: 71
  • Watchers: 7
  • Forks: 27
  • Open Issues: 0
  • Releases: 0
Archived
Created over 10 years ago · Last pushed about 2 years ago
Metadata Files
Readme

README.md

UAVPathOptimization

This code was developed in conjunction with our paper

Ingersoll, B., Ingersoll, K., DeFranco, P., and Ning, A., “UAV Path-Planning Using Bézier Curves and a Receding Horizon Approach,” AIAA Modeling and Simulation Technologies Conference, Washington, DC, Jun. 2016. doi:10.2514/6.2016-3675

Given a flight domain of static and/or dynamic obstacles, the method attempts to find a viable flight path while minimizing some criteria, such as path length, time elapsed, or energy use.

To use the path-planning algorithm, open main.m. Add the subfolders in \src and then run main.m. To preview possible obstacle fields, use test.m.

In main.m, there are several different algorithm options, such as which objective function will be used, how the gradients will be calculated, what type of obstacle field will be used, etc. Once the algorithm is complete, plots are generated which show the UAV's planned path.

Owner

  • Name: BYU FLOW Lab
  • Login: byuflowlab
  • Kind: organization
  • Location: Provo, UT

FLight, Optimization, and Wind

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