1 code implementation • 7 Jun 2021 • 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 synthesis.
1 code implementation • 1 Jun 2020 • Valentin Peretroukhin, Matthew Giamou, David M. Rosen, W. Nicholas Greene, Nicholas Roy, Jonathan Kelly
Accurate rotation estimation is at the heart of robot perception tasks such as visual odometry and object pose estimation.
1 code implementation • 27 Feb 2020 • 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.
Robotics
1 code implementation • 1 Oct 2019 • Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
We present two novel techniques for detecting zero-velocity events to improve foot-mounted inertial navigation.
Robotics Signal Processing
1 code implementation • 2 Apr 2019 • Matthew Giamou, Filip Maric, Valentin Peretroukhin, Jonathan Kelly
Estimating unknown rotations from noisy measurements is an important step in SfM and other 3D vision tasks.
no code implementations • 1 Apr 2019 • Valentin Peretroukhin, Brandon Wagstaff, Matthew Giamou, Jonathan Kelly
Accurate estimates of rotation are crucial to vision-based motion estimation in augmented reality and robotics.
1 code implementation • 10 Sep 2018 • Matthew Giamou, Ziye Ma, Valentin Peretroukhin, Jonathan Kelly
We present a certifiably globally optimal algorithm for determining the extrinsic calibration between two sensors that are capable of producing independent egomotion estimates.
Robotics
1 code implementation • 10 Sep 2017 • Valentin Peretroukhin, Jonathan Kelly
We use this loss to train a Deep Pose Correction network (DPC-Net) that predicts corrections for a particular estimator, sensor and environment.
no code implementations • 1 Aug 2017 • Valentin Peretroukhin, Lee Clement, Matthew Giamou, Jonathan Kelly
Navigation in unknown, chaotic environments continues to present a significant challenge for the robotics community.
no code implementations • 1 Aug 2017 • Valentin Peretroukhin, William Vega-Brown, Nicholas Roy, Jonathan Kelly
Many algorithms in computer vision and robotics make strong assumptions about uncertainty, and rely on the validity of these assumptions to produce accurate and consistent state estimates.
1 code implementation • 4 Jul 2017 • 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 classification of motion type.
Robotics Human-Computer Interaction
2 code implementations • 20 Sep 2016 • Valentin Peretroukhin, Lee Clement, Jonathan Kelly
We present a method to incorporate global orientation information from the sun into a visual odometry pipeline using only the existing image stream, where the sun is typically not visible.
no code implementations • 15 Sep 2016 • Lee Clement, Valentin Peretroukhin, Jonathan Kelly
In the absence of reliable and accurate GPS, visual odometry (VO) has emerged as an effective means of estimating the egomotion of robotic vehicles.