Applied Mathematics Seminar——Non-convex Pose Graph Optimization in SLAM via Proximal Linearized Riemannian ADMM
报告人：韩德仁 （北京航空航天大学）
时间：2026-03-25 16:00-17:00
地点：智华楼-王选报告厅-101
Abstract:
Pose graph optimization (PGO) is a well-known technique for solving the pose-based simultaneous localization and mapping (SLAM) problem. In this paper, we represent the rotation and translation by a unit quaternion and a three-dimensional vector, and propose a new PGO model based on the von Mises-Fisher distribution. The constraints derived from the unit quaternions are spherical manifolds, and the projection onto the constraints can be calculated by normalization. Then a proximal linearized Riemannian alternating direction method of multipliers (PieADMM) is developed to solve the proposed model, which not only has low memory requirements, but also can update the poses in parallel. Furthermore, we establish the iteration complexity of of PieADMM for finding an ϵ-stationary solution of our model. The efficiency of our proposed algorithm is demonstrated by numerical experiments on two synthetic and four 3D SLAM benchmark datasets.
简介：
韩德仁，教授，博士生导师，北京航空航天大学数学科学学院院长。研究方向为大规模优化问题、变分不等式问题及其在交通规划、磁共振成像中的应用。获教育部科学研究优秀成果奖二等奖、江苏省科学技术奖、中国运筹学会青年科技奖等奖项；主持国家自然科学基金重点项目、杰出青年基金项目等多项项目。担任中国运筹学会副理事长、算法软件与应用分会理事长；中国工业与应用数学学会常务理事；《数值计算与计算机应用》、《Journal of the Operations Research Society of China》、《Journal of Global Optimization》、《Asia-Pacific Journal of Operational Research》编委。
