human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "intrinsic filtering on lie groups with applications to attitude estimation"
  Abstract: This paper proposes a probabilistic approach to the problem of intrinsic filtering of a system on a matrix Lie group with invariance properties. The problem of an invariant continuous-time model with discrete-time measurements is cast into a rigorous stochastic and geometric framework. Building upon the theory of continuous-time invariant observers, we show that, as in the linear case, the error equation is a Markov chain that does not depend on the state estimate. Thus, when the filter's gains are held fixed, and the filter admits almost-global convergence properties with noise turned off, the noisy error's distribution is proved to converge to a stationary distribution, providing insight into the mathematical theory of filtering on Lie groups. For engineering purposes we also introduce the discrete-time Invariant Extended Kalman Filter, for which the trusted covariance matrix is shown to asymptotically converge, and some numerically more involved sample-based methods as well to compute the Kalman gains. The methods are applied to attitude estimation, allowing to derive novel theoretical results in this field, and illustrated through simulations on synthetic data.

Connected through hyperedge HE-1 (induced by source paper "a code for unscented kalman filtering on manifolds ukf m"):
  with members:
    - "exploiting symmetries to design ekfs with consistency properties for navigation and slam"
    - "contact aided invariant extended kalman filtering for legged robot state estimation"
    - "a micro lie theory for state estimation in robotics"
    - "an ekf slam algorithm with consistency properties"
    - "quaternion kinematics for the error state kalman filter"
    - "the invariant extended kalman filter as a stable observer"
    - "integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds"

Connected through hyperedge HE-2 (induced by source paper "a mathematical framework for imu error propagation with applications to preintegration"):
  with members:
    - "closed form preintegration methods for graph based visual inertial navigation"
    - "contact aided invariant extended kalman filtering for legged robot state estimation"
    - "an invariant linear quadratic gaussian controller for a simplified car"
    - "the invariant extended kalman filter as a stable observer"
    - "integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds"

Connected through hyperedge HE-3 (induced by source paper "invariant smoothing on lie groups"):
  with members:
    - "on manifold preintegration for real time visual inertial odometry"
    - "an ekf slam algorithm with consistency properties"
    - "an invariant linear quadratic gaussian controller for a simplified car"
    - "the invariant extended kalman filter as a stable observer"
    - "integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds"

Connected through hyperedge HE-4 (induced by source paper "a discrete time attitude observer on so 3 for vision and gps fusion"):
  with members:
    - "observers for invariant systems on lie groups with biased input measurements and homogeneous outputs"
    - "orb slam a versatile and accurate monocular slam system"

Connected through hyperedge HE-5 (induced by source paper "mixture reduction on matrix lie groups"):
  with members:
    - "moving object tracking employing rigid body motion on matrix lie groups"

Connected through hyperedge HE-6 (induced by source paper "an ekf slam algorithm with consistency properties"):
  with members:
    - "invariant ekf design for scan matching aided localization"
    - "an invariant linear quadratic gaussian controller for a simplified car"
    - "the invariant extended kalman filter as a stable observer"

Connected through hyperedge HE-7 (induced by source paper "the invariant extended kalman filter as a stable observer"):
  with members:
    - "invariant ekf design for scan matching aided localization"
    - "accurate 3d maps from depth images and motion sensors via nonlinear kalman filtering"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SY(Systems and Control)