139 citations · 421 across the 12 of their papers we have counts for
8 papers · 1 filter
A Self-Supervised, Differentiable Kalman Filter for Uncertainty-Aware Visual-Inertial Odometry
Brandon Wagstaff, Emmett Wise, Jonathan Kelly
Visual-inertial odometry (VIO) systems traditionally rely on filtering or optimization-based techniques for egomotion estimation. While these methods are accurate under nominal con…
Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching
Justin Tomasi, Brandon Wagstaff, Steven L. Waslander +1
Successful visual navigation depends upon capturing images that contain sufficient useful information. In this letter, we explore a data-driven approach to account for environmenta…
Self-Supervised Scale Recovery for Monocular Depth and Egomotion Estimation
Brandon Wagstaff, Jonathan Kelly
The self-supervised loss formulation for jointly training depth and egomotion neural networks with monocular images is well studied and has demonstrated state-of-the-art accuracy.…
Heteroscedastic Uncertainty for Robust Generative Latent Dynamics
Oliver Limoyo, Bryan Chan, Filip Marić +3
Learning or identifying dynamics from a sequence of high-dimensional observations is a difficult challenge in many domains, including reinforcement learning and control. The proble…
Self-Supervised Deep Pose Corrections for Robust Visual Odometry
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
We present a self-supervised deep pose correction (DPC) network that applies pose corrections to a visual odometry estimator to improve its accuracy. Instead of regressing inter-fr…
Robust Data-Driven Zero-Velocity Detection for Foot-Mounted Inertial Navigation
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
We present two novel techniques for detecting zero-velocity events to improve foot-mounted inertial navigation. Our first technique augments a classical zero-velocity detector by i…
LSTM-Based Zero-Velocity Detection for Robust Inertial Navigation
Brandon Wagstaff, Jonathan Kelly
We present a method to improve the accuracy of a zero-velocity-aided inertial navigation system (INS) by replacing the standard zero-velocity detector with a long short-term memory…
Improving Foot-Mounted Inertial Navigation Through Real-Time Motion Classification
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
We present a method to improve the accuracy of a foot-mounted, zero-velocity-aided inertial navigation system (INS) by varying estimator parameters based on a real-time classificat…