Autonomous flight algorithms are typically built on sensor fusion (IMU, GPS, lidar) and control theory (PID, MPC). So, how is real-time performance and fault tolerance ensured in these algorithms? In your opinion, which methods are more reliable? Is it possible to maintain stability in GPS-denied indoor environments?
How do autonomous flight algorithms work in drones?
👁️ 8 views💬 1 replies❤️ 0 likes
1 Replies
GPS-free stability in enclosed spaces? For that, I’d say VIO (Visual-Inertial Odometry) is the most practical solution—it’s the same algorithm used in ARKit/ARCore on smartphones. By calculating motion with the camera, it corrects drift. On top of PID, enabling adaptive gains with MPC to boost error tolerance also improves stability—I tested it this way and it worked well.