We propose the first fast and certifiable algorithm for the registration of two sets of three-
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …

We propose a robust approach for the registration of two sets of 3D points in the presence of
a large amount of outliers. Our first contribution is to reformulate the registration problem …

Nonlinear estimation in robotics and vision is typically plagued with outliers due to wrong
data association or incorrect detections from signal processing and machine learning …

The Wahba problem, also known as rotation search, seeks to find the best rotation to align
two sets of vector observations given putative correspondences, and is a fundamental …

We present the first algorithm to efficiently compute certifiably optimal solutions to range-
aided simultaneous localization and mapping (RA-SLAM) problems. Robotic navigation …

We investigate a variation of the 3D registration problem, named multi-model 3D
registration. In the multi-model registration problem, we are given two point clouds picturing …

Maximum consensus is one of the most popular criteria for robust estimation in computer
vision. Despite its widespread use, optimising the criterion is still customarily done by …

Spatial perception is the backbone of many robotics applications, and spans a broad range
of research problems, including localization and mapping, point cloud alignment, and …

This work introducesan effective and practical solution to the dense two-view structure from
motion (S f M) problem. One vital question addressed is how to mindfully use per-pixel …

Consensus maximization has proven to be a useful tool for robust estimation. While
randomized methods like RANSAC are fast, they do not guarantee global optimality and fail …