Constraint Manifolds for Robotic Inference and Planning

2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA(2023)

引用 1|浏览22
暂无评分
摘要
We propose a manifold optimization approach for solving constrained inference and planning problems. The approach employs a framework that transforms an arbitrary nonlinear equality constrained optimization problem into an unconstrained manifold optimization problem. The core of the transformation process is the formulation of constraint manifolds that represent sets of variables subject to equality constraints. We propose various approaches to define the tangent spaces and retraction operations of constraint manifolds, which are crucial for manifold optimization. We evaluate our constraint manifold optimization approach on multiple constrained inference and planning problems, and show that it generates strictly feasible results with increased efficiency as compared to state-of-the-art constrained optimization methods.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要