🤖 AI Summary
Monocular visual-inertial odometry struggles to recover metric scale from vision alone, and the relationship between scale observability and trajectory characteristics remains unclear. This work addresses this gap through an observability analysis, revealing that translational acceleration induced by trajectory curvature is the key factor coupling scale with inertial states. Leveraging the asymmetry between gravity and linear acceleration in the IMU model, the study establishes a theoretical framework and, for the first time, explicitly identifies trajectory curvature as the decisive contributor to scale observability. A lightweight trajectory excitation metric is proposed, computable directly from raw IMU data. Experiments on straight, circular, and figure-eight trajectories yield scale errors of 9.2%, 6.4%, and 4.8%, respectively, with excitation levels spanning four orders of magnitude, thereby validating the effectiveness of trajectory design in enhancing scale recovery accuracy.
📝 Abstract
Monocular visual-inertial odometry (VIO) cannot recover metric scale from vision alone; scale must be resolved through inertial measurements. We present a trajectory-dependent observability analysis showing that translational acceleration, produced by curvature, not constant-speed straight-line travel, is the fundamental source that couples scale to the inertial state. This relationship is formalized through the gravity-acceleration asymmetry in the IMU model, from which we derive rank conditions on the observability matrix and propose a lightweight excitation metric computable from raw IMU data. Controlled experiments on a differential-drive robot with a monocular camera and consumer-grade IMU validate the theory, with straight-line motion yielding 9.2% scale error, circular motion 6.4%, and figure-eight motion 4.8%, with excitation spanning four orders of magnitude. These results establish trajectory design as a practical mechanism for improving metric scale recovery.