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: "integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds"
  Abstract: Common estimation algorithms, such as least squares estimation or the Kalman filter, operate on a state in a state space S that is represented as a real-valued vector. However, for many quantities, most notably orientations in 3D, S is not a vector space, but a so-called manifold, i.e. it behaves like a vector space locally but has a more complex global topological structure. For integrating these quantities, several ad-hoc approaches have been proposed. #R##N#Here, we present a principled solution to this problem where the structure of the manifold S is encapsulated by two operators, state displacement [+]:S x R^n --> S and its inverse [-]: S x S --> R^n. These operators provide a local vector-space view \delta; --> x [+] \delta; around a given state x. Generic estimation algorithms can then work on the manifold S mainly by replacing +/- with [+]/[-] where appropriate. We analyze these operators axiomatically, and demonstrate their use in least-squares estimation and the Unscented Kalman Filter. Moreover, we exploit the idea of encapsulation from a software engineering perspective in the Manifold Toolkit, where the [+]/[-] operators mediate between a "flat-vector" view for the generic algorithm and a "named-members" view for the problem specific functions.

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"
    - "intrinsic filtering on lie groups with applications to attitude estimation"

Connected through hyperedge HE-2 (induced by source paper "least squares optimization from theory to practice"):
  with members:
    - "proslam graph slam from a programmer s perspective"
    - "a general framework for flexible multi cue photometric point cloud registration"

Connected through hyperedge HE-3 (induced by source paper "closed form preintegration methods for graph based visual inertial navigation"):
  with members:
    - "stereo dso large scale direct sparse visual odometry with stereo cameras"
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"
    - "on manifold preintegration for real time visual inertial odometry"
    - "direct sparse odometry"
    - "past present and future of simultaneous localization and mapping toward the robust perception age"
    - "faster and better a machine learning approach to corner detection"

Connected through hyperedge HE-4 (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"
    - "intrinsic filtering on lie groups with applications to attitude estimation"

Connected through hyperedge HE-5 (induced by source paper "invariant cubature kalman filter for monocular visual inertial odometry with line features"):
  with members:
    - "vins mono a robust and versatile monocular visual inertial state estimator"
    - "on manifold preintegration for real time visual inertial odometry"
    - "an ekf slam algorithm with consistency properties"

Connected through hyperedge HE-6 (induced by source paper "manifold geometry with fast automatic derivatives and coordinate frame semantics checking in c"):
  with members:
    - "a primer on the differential calculus of 3d orientations"
    - "automatic differentiation in machine learning a survey"
    - "the stan math library reverse mode automatic differentiation in c"
    - "expression templates revisited a performance analysis of current methodologies"
    - "efficient expression templates for operator overloading based automatic differentiation"

Connected through hyperedge HE-7 (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"
    - "intrinsic filtering on lie groups with applications to attitude estimation"

Connected through hyperedge HE-8 (induced by source paper "visual slam based localization and navigation for service robots the pepper case"):
  with members:
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"
    - "visual inertial monocular slam with map reuse"
    - "past present and future of simultaneous localization and mapping toward the robust perception age"
    - "orb slam a versatile and accurate monocular slam system"

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)