human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "analytical slam without linearization"):
  Abstract: This paper solves the classical problem of simultaneous localization and mapping (SLAM) in a fashion which avoids linearized approximations altogether. Based on creating virtual synthetic measurements, the algorithm uses a linear time- varying (LTV) Kalman observer, bypassing errors and approximations brought by the linearization process in traditional extended Kalman filtering (EKF) SLAM. Convergence rates of the algorithm are established using contraction analysis. Different combinations of sensor information can be exploited, such as bearing measurements, range measurements, optical flow, or time-to-contact. As illustrated in simulations, the proposed algorithm can solve SLAM problems in both 2D and 3D scenarios with guaranteed convergence rates in a full nonlinear context.

Includes members:
  Member "simultaneous localization and mapping without linearization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "numerical and experimental realization of analytical slam")
  Member "rao blackwellised particle filtering for dynamic bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "poserbpf a rao blackwellized particle filter for 6d object pose tracking")
  Member "estimating uncertain spatial relationships in robotics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two body problem collaborative visual task completion")
  Member "efficient touch based localization through submodularity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "in hand object pose tracking via contact feedback and gpu accelerated robotic simulation")
  Member "from angular manifolds to the integer lattice guaranteed orientation estimation with application to pose graph optimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improved pose graph optimization for planar motions using riemannian geometry on the manifold of dual quaternions")

Question: Please tell me which class the source paper 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)