Flight Dynamics-based Recovery of a UAV Trajectory using Ground Cameras

TL;DR

This paper introduces a novel ground-camera-based method for estimating UAV trajectories by combining structure from motion with flight dynamics, enabling control inference without perfect tracking.

Contribution

It presents a new bundle adjustment technique that incorporates flight dynamics as a prior, improving 3D trajectory reconstruction and control inference for UAVs.

Findings

Effective in real and simulated environments

Does not require perfect single-view tracking

Infers control inputs from trajectory data

Abstract

We propose a new method to estimate the 6-dof trajectory of a flying object such as a quadrotor UAV within a 3D airspace monitored using multiple fixed ground cameras. It is based on a new structure from motion formulation for the 3D reconstruction of a single moving point with known motion dynamics. Our main contribution is a new bundle adjustment procedure which in addition to optimizing the camera poses, regularizes the point trajectory using a prior based on motion dynamics (or specifically flight dynamics). Furthermore, we can infer the underlying control input sent to the UAV's autopilot that determined its flight trajectory. Our method requires neither perfect single-view tracking nor appearance matching across views. For robustness, we allow the tracker to generate multiple detections per frame in each video. The true detections and the data association across videos is estimated using robust multi-view triangulation and subsequently refined during our bundle adjustment procedure. Quantitative evaluation on simulated data and experiments on real videos from indoor and outdoor scenes demonstrates the effectiveness of our method.