Simultaneous localization and mapping (SLAM) is the process of constructing a global
model of an environment from local observations of it; this is a foundational capability for …

This article presents the first certifiably correct algorithm for distributed pose-graph
optimization (PGO), the backbone of modern collaborative simultaneous localization and …

We address rotation averaging (RA) and its application to real-world 3D reconstruction.
Local optimisation based approaches are the de facto choice, though they only guarantee a …

Block coordinate descent is an optimization paradigm that iteratively updates one block of
variables at a time, making it quite amenable to big data applications due to its scalability …

In recent years, many estimation problems in robotics have been shown to be solvable to
global optimality using their semidefinite relaxations. However, the runtime complexity of off …

This paper explores the distance-based relative state estimation problem in large-scale
systems, which is hard to solve effectively due to its high-dimensionality and non-convexity …

This paper presents the first certifiably correct solver for distributed rotation and pose
synchronization, the backbone of modern collaborative simultaneous localization and …

Collaborative geometric estimation, which enables multiple agents to construct globally
consistent geometric models of the environment (eg, maps and robot poses) from noisy local …

Estimating unknown rotations from noisy measurements is an important step in SfM and
other 3D vision tasks. Typically, local optimization methods susceptible to returning …