Selecting good measurements via ℓ1 relaxation: A convex approach for robust estimation over graphs
Pose graph optimization is an elegant and efficient formulation for robot localization and
map**. Experimental evidence suggests that, in real problems, the set of measurements …
map**. Experimental evidence suggests that, in real problems, the set of measurements …
Expectation-maximization for adaptive mixture models in graph optimization
Non-Gaussian and multimodal distributions are an important part of many recent robust
sensor fusion algorithms. In difference to robust cost functions, they are probabilistically …
sensor fusion algorithms. In difference to robust cost functions, they are probabilistically …
Constructing category-specific models for monocular object-slam
We present a new paradigm for real-time object-oriented SLAM with a monocular camera.
Contrary to previous approaches, that rely on object-level models, we construct category …
Contrary to previous approaches, that rely on object-level models, we construct category …
Factor graph based 3d multi-object tracking in point clouds
Accurate and reliable tracking of multiple moving objects in 3D space is an essential
component of urban scene understanding. This is a challenging task because it requires the …
component of urban scene understanding. This is a challenging task because it requires the …
A high-precision LiDAR-inertial odometry via Kalman filter and factor graph optimization
J Tang, X Zhang, Y Zou, Y Li, G Du - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
For simultaneous localization and map** (SLAM) in large-scale scenarios, the influence of
long-distance and high-speed motion cannot be ignored because the risk of huge odometry …
long-distance and high-speed motion cannot be ignored because the risk of huge odometry …
A comparison of graph optimization approaches for pose estimation in SLAM
Simultaneous localization and map** (SLAM) is an important tool that enables
autonomous navigation of mobile robots through unknown environments. As the name …
autonomous navigation of mobile robots through unknown environments. As the name …
Low-latency Visual-based High-Quality 3D Reconstruction using Point Cloud Optimization
P Chi, Z Wang, H Liao, T Li, J Zhan, X Wu… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
In recent years, 3-D reconstruction has been widely used in robot pose estimation, mine
exploration, building of digital twins, and other fields. Visual-based reconstruction methods …
exploration, building of digital twins, and other fields. Visual-based reconstruction methods …
Opt: A domain specific language for non-linear least squares optimization in graphics and imaging
Many graphics and vision problems can be expressed as non-linear least squares
optimizations of objective functions over visual data, such as images and meshes. The …
optimizations of objective functions over visual data, such as images and meshes. The …
Megba: A gpu-based distributed library for large-scale bundle adjustment
Abstract Large-scale Bundle Adjustment (BA) requires massive memory and computation
resources which are difficult to be fulfilled by existing BA libraries. In this paper, we propose …
resources which are difficult to be fulfilled by existing BA libraries. In this paper, we propose …
What localizes beneath: A metric multisensor localization and map** system for autonomous underground mining vehicles
Robustly and accurately localizing vehicles in underground mines is particularly challenging
due to the unavailability of GPS, variable and often poor lighting conditions, visual aliasing …
due to the unavailability of GPS, variable and often poor lighting conditions, visual aliasing …