yrlu/quadrotor
Quadrotor control, path planning and trajectory optimization observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3405
- days_rel: n/a
- days_push: 851
- n_releases_24m: 0
Adoption not part of the score
1126 stars · 302 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A MATLAB codebase implementing quadrotor PD controllers, path planning algorithms (Dijkstra, A*), and trajectory optimization (minimum snap/acceleration). Developed as coursework for UPenn's MEAM 620 Advanced Robotics course.
Use cases
- simulate quadrotor flight control in matlab
- implement pd controller for drone
- plan paths with dijkstra or a star
- generate minimum snap trajectory for quadrotor
- learn robotics trajectory optimization
- reference implementation for uav control course assignments
When to choose
- you need educational MATLAB reference code for quadrotor control and planning
- you want to study minimum snap trajectory generation
- you are working through a robotics course on UAV control
When to avoid
- you need production-ready flight software for a real drone
- you need code in Python or C++ rather than MATLAB
- you need an actively maintained project with a license
Facets
library · maturity maintenance
simulation robotics machine-learning robotics simulation education cross-platform quadrotor uav drone pd-controller path-planning dijkstra astar trajectory-optimization minimum-snap matlab algorithms
1 source
- readme: https://github.com/yrlu/quadrotor · fetched 2026-08-28 · 73765a496482
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| yrlu/quadrotor | main | 23 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem