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: "an invariant linear quadratic gaussian controller for a simplified car"
  Abstract: In this paper, we consider the problem of tracking a reference trajectory for a simplified car model based on unicycle kinematics, whose position only is measured, and where the control input and the measurements are corrupted by independent Gaussian noises. To tackle this problem we devise a novel observer-controller: the invariant Linear Quadratic Gaussian controller (ILQG). It is based on the Linear Quadratic Gaussian controller, but the equations are slightly modified to account for, and to exploit, the symmetries of the problem. The gain tuning exhibits a reduced dependency on the estimated trajectory, and is thus less sensitive to misestimates. Beyond the fact the invariant approach is sensible (there is no reason why the controller performance should depend on whether the reference trajectory is heading west or south), we show through simulations that the ILQG outperforms the conventional LQG controller in case of large noises or large initial uncertainties. We show that those robustness properties may also prove useful for motion planning applications.

Connected through hyperedge HE-1 (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"
    - "the invariant extended kalman filter as a stable observer"
    - "intrinsic filtering on lie groups with applications to attitude estimation"
    - "integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds"

Connected through hyperedge HE-2 (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"
    - "the invariant extended kalman filter as a stable observer"
    - "intrinsic filtering on lie groups with applications to attitude estimation"
    - "integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds"

Connected through hyperedge HE-3 (induced by source paper "an ekf slam algorithm with consistency properties"):
  with members:
    - "invariant ekf design for scan matching aided localization"
    - "the invariant extended kalman filter as a stable observer"
    - "intrinsic filtering on lie groups with applications to attitude estimation"

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.RO(Robotics)