87 citations · 385 across the 13 of their papers we have counts for
13 papers
Convex Iteration for Distance-Geometric Inverse Kinematics
Matthew Giamou, Filip Marić, David M. Rosen +4
Inverse kinematics (IK) is the problem of finding robot joint configurations that satisfy constraints on the position or pose of one or more end-effectors. For robots with redundan…
On the Coupling of Depth and Egomotion Networks for Self-Supervised Structure from Motion
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
Structure from motion (SfM) has recently been formulated as a self-supervised learning problem, where neural network models of depth and egomotion are learned jointly through view…
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty
Valentin Peretroukhin, Matthew Giamou, David M. Rosen +3
Accurate rotation estimation is at the heart of robot perception tasks such as visual odometry and object pose estimation. Deep neural networks have provided a new way to perform t…
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…
Probabilistic Regression of Rotations using Quaternion Averaging and a Deep Multi-Headed Network
Valentin Peretroukhin, Brandon Wagstaff, Matthew Giamou +1
Accurate estimates of rotation are crucial to vision-based motion estimation in augmented reality and robotics. In this work, we present a method to extract probabilistic estimates…