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 "robust visual inertial slam combination of ekf and optimization method"):
  Abstract: This paper has presented a novel tightly-coupled monocular visual-inertial Simultaneous Localization and Mapping(SLAM) algorithm combining the advantages of both filtering methods and optimization methods. Our approach uses IMU assisted visual EKF SLAM method in the front-end to estimate the pose and velocity at frame rate. In the back-end, the standard approaches such as nonlinear optimization as well as loop closure have been used to obtain accurate trajectory of the sensor and 3D map of the environment. We also propose a novel scale computation approach that can accurately initialize the scale in short time. In addition, the optimized map points have been used to improve the accuracy of the filter. We evaluated the algorithm on a public dataset, when compared to other state-of-the-art monocular Visual-Inertial SLAM approaches, our algorithm achieves unprecedented accuracy and robustness.

Includes members:
  Member "visual inertial monocular slam with map reuse":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")
  Member "orb slam a versatile and accurate monocular slam system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")

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)