Apr 29, 2024 · View a PDF of the paper titled Non-convex Pose Graph Optimization in SLAM via Proximal Linearized Riemannian ADMM, by Xin Chen and 3 other authors

Jun 27, 2025 · Pose graph optimization in SLAM is a special non-convex optimization. In this paper, we propose a new non-convex pose graph optimization model based on augmented …

Top navigation bar lets you select the following sections: Industrial Optimization Solving hard commercial optimization problems using hybrid solvers. Quantum Research Using the …

Jul 16, 2020 · This video provides some intuition around Pose Graph Optimization - a popular framework for solving the simultaneous localization and mapping (SLAM) problem in …

In graph-based SLAM, we build the graph and find a node configuration that minimizes the error introduced by the constraints. Once we have the graph, we determine the most likely map by …

We have covered two common scenarios found in SLAM: Pose Graph SLAM and Landmark based SLAM using synthetic dataset. The main goal is to cover how to formulate a graph …

Sep 30, 2014 · If robot orientations were known, pose graph optimization would be a linear least-squares problem, whose solution can be computed efficiently and reliably. Since rotations are …

Our approach uses an iterative nonlinear optimization algorithm similar to stochastic gradient descent. In short, constraints in the pose graph are considered one at a time: each constraint …

Let V be the set of pose graph edges. Then the goal of pose graph optimization is to find such x that minimizes the negative log-likelihood function of all the observations.

We propose a non-convex pose graph optimization model based on augmented unit quaternion and vMF distribution, in which the data storage is low-cost and the projection of unit …