Solving hard problems in robotics – with a little help from semidefinite relaxations, nullspaces, and sparsity
Event details
| Date | 12.03.2024 |
| Hour | 16:15 |
| Speaker | Frederike Duembgen (Université de Toronto) |
| Location |
CM1517
|
| Category | Conferences - Seminars |
| Event Language | English |
Abstract: Many state estimation and planning tasks in robotics are formulated as non-convex optimization problems, and commonly deployed efficient solvers may converge to poor local minima. Recent years have seen promising developments in so-called certifiably optimal estimation, showing that many problems can in fact be solved to global optimality or certified through the use of tight semidefinite relaxations.
In this talk, I present our efforts to make such methods – for the field of state estimation in particular – more practical for roboticists. Among those efforts, I will present novel efficient optimality certificates as a low-cost add-on to off-the-shelf local solvers, which apply to a variety of problems including range-only, stereo-camera and, more generally, matrix-weighted localization. Then, I present our approach to automatically certify almost any state estimation problem, using a sampling-based method to automatically find tight relaxations through nullspace characterizations. I end with an overview of our most recent work, which allows to create both fast and certifiably optimal solvers by exploiting the sparse problem structure.
In this talk, I present our efforts to make such methods – for the field of state estimation in particular – more practical for roboticists. Among those efforts, I will present novel efficient optimality certificates as a low-cost add-on to off-the-shelf local solvers, which apply to a variety of problems including range-only, stereo-camera and, more generally, matrix-weighted localization. Then, I present our approach to automatically certify almost any state estimation problem, using a sampling-based method to automatically find tight relaxations through nullspace characterizations. I end with an overview of our most recent work, which allows to create both fast and certifiably optimal solvers by exploiting the sparse problem structure.
Practical information
- General public
- Free
Organizer
- Nicolas Boumal
Contact
- Nicolas Boumal, Séverine Eggli