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: "simultaneous merging multiple grid maps using the robust motion averaging"
  Abstract: Mapping in the GPS-denied environment is an important and challenging task in the field of robotics. In the large environment, mapping can be significantly accelerated by multiple robots exploring different parts of the environment. Accordingly, a key problem is how to integrate these local maps built by different robots into a single global map. In this paper, we propose an approach for simultaneous merging of multiple grid maps by the robust motion averaging. The main idea of this approach is to recover all global motions for map merging from a set of relative motions. Therefore, it firstly adopts the pair-wise map merging method to estimate relative motions for grid map pairs. To obtain as many reliable relative motions as possible, a graph-based sampling scheme is utilized to efficiently remove unreliable relative motions obtained from the pair-wise map merging. Subsequently, the accurate global motions can be recovered from the set of reliable relative motions by the motion averaging. Experimental results carried on real robot data sets demonstrate that the proposed approach can achieve simultaneous merging of multiple grid maps with good performances.

Connected through hyperedge HE-1 (induced by source paper "registration of multi view point sets under the perspective of expectation maximization"):
  with members:
    - "joint alignment of multiple point sets with batch and incremental expectation maximization"
    - "filterreg robust and efficient probabilistic point set registration using gaussian filter and twist parameterization"
    - "weighted motion averaging for the registration of multi view range scans"
    - "go icp a globally optimal solution to 3d icp point set registration"
    - "bundlefusion real time globally consistent 3d reconstruction using on the fly surface re integration"
    - "point set registration coherent point drift"
    - "on the closed form solution of the rotation matrix arising in computer vision problems"

Connected through hyperedge HE-2 (induced by source paper "collaborative slam based on wifi fingerprint similarity and motion information"):
  with members:
    - "cooperative relative positioning of mobile users by fusing imu inertial and uwb ranging information"
    - "rfm slam exploiting relative feature measurements to separate orientation and position estimation in slam"
    - "modern wlan fingerprinting indoor positioning methods and deployment challenges"
    - "past present and future of simultaneous localization and mapping toward the robust perception age"

Connected through hyperedge HE-3 (induced by source paper "information correlated levy walk exploration and distributed mapping using a swarm of robots"):
  with members:
    - "dynamic topological mapping with biobotic swarms"

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.AI(Artificial Intelligence)