233 citations · 507 across the 6 of their papers we have counts for
6 papers
TLIO: Tight Learned Inertial Odometry
Wenxin Liu, David Caruso, Eddy Ilg +5
In this work we propose a tightly-coupled Extended Kalman Filter framework for IMU-only state estimation. Strap-down IMU measurements provide relative state estimates based on IMU…
Learning to Align Images using Weak Geometric Supervision
Jing Dong, Byron Boots, Frank Dellaert +2
Image alignment tasks require accurate pixel correspondences, which are usually recovered by matching local feature descriptors. Such descriptors are often derived using supervised…
STEAP: simultaneous trajectory estimation and planning
Mustafa Mukadam, Jing Dong, Frank Dellaert +1
We present a unified probabilistic framework for simultaneous trajectory estimation and planning (STEAP). Estimation and planning problems are usually considered separately, howeve…
Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference
Mustafa Mukadam, Jing Dong, Xinyan Yan +2
We introduce a novel formulation of motion planning, for continuous-time trajectories, as probabilistic inference. We first show how smooth continuous-time trajectories can be repr…
Sparse Gaussian Processes for Continuous-Time Trajectory Estimation on Matrix Lie Groups
Jing Dong, Byron Boots, Frank Dellaert
Continuous-time trajectory representations are a powerful tool that can be used to address several issues in many practical simultaneous localization and mapping (SLAM) scenarios,…
4D Crop Monitoring: Spatio-Temporal Reconstruction for Agriculture
Jing Dong, John Gary Burnham, Byron Boots +2
Autonomous crop monitoring at high spatial and temporal resolution is a critical problem in precision agriculture. While Structure from Motion and Multi-View Stereo algorithms can…