Amos-Chen98/neo-planner
[IROS'25] Learning to Initialize Trajectory Optimization for Vision-Based Autonomous Flight in Unknown Environments
This project helps operations engineers and drone researchers develop and test autonomous drone navigation systems. It takes in visual sensor data from a drone operating in an unknown environment and outputs optimized flight trajectories, enabling drones to navigate autonomously and track moving objects while avoiding obstacles. The primary users are professionals working with unmanned aerial vehicles (UAVs) in simulation and real-world testing.
Use this if you are developing or testing autonomous drone navigation systems and need a robust framework for trajectory optimization and obstacle avoidance, especially for vision-based flight in unfamiliar settings.
Not ideal if you are looking for an out-of-the-box solution for drone delivery or agricultural surveying without further development.
Stars
27
Forks
—
Language
Python
License
GPL-3.0
Category
Last pushed
Jan 08, 2026
Commits (30d)
0
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