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: "nimbro rescue solving disaster response tasks through mobile manipulation robot momaro"
  Abstract: Robots that solve complex tasks in environments too dangerous for humans to enter are desperately needed, e.g. for search and rescue applications. We describe our mobile manipulation robot Momaro, with which we participated successfully in the DARPA Robotics Challenge. It features a unique locomotion design with four legs ending in steerable wheels, which allows it both to drive omnidirectionally and to step over obstacles or climb. Furthermore, we present advanced communication and teleoperation approaches, which include immersive 3D visualization, and 6D tracking of operator head and arm motions. The proposed system is evaluated in the DARPA Robotics Challenge, the DLR SpaceBot Cup Qualification and lab experiments. We also discuss the lessons learned from the competitions.

Connected through hyperedge HE-1 (induced by source paper "remote mobile manipulation with the centauro robot full body telepresence and autonomous operator assistance"):
  with members:
    - "planning hybrid driving stepping locomotion on multiple levels of abstraction"
    - "transferring category based functional grasping skills by latent space non rigid registration"
    - "fast object learning and dual arm coordination for cluttered stowing picking and packing"
    - "supervised autonomous locomotion and manipulation for disaster response with a centaur like robot"
    - "autonomous dual arm manipulation of familiar objects"
    - "transferring grasping skills to novel instances by latent space non rigid registration"
    - "anytime hybrid driving stepping locomotion planning"
    - "point set registration coherent point drift"

Connected through hyperedge HE-2 (induced by source paper "rgb d object detection and semantic segmentation for autonomous manipulation in clutter"):
  with members:
    - "mask r cnn"
    - "ssd single shot multibox detector"
    - "refinenet multi path refinement networks for high resolution semantic segmentation"
    - "a summary of team mit s approach to the amazon picking challenge 2015"
    - "iterative visual recognition for learning based randomized bin picking"
    - "multi view self supervised deep learning for 6d pose estimation in the amazon picking challenge"
    - "team delft s robot winner of the amazon picking challenge 2016"
    - "densecap fully convolutional localization networks for dense captioning"

Connected through hyperedge HE-3 (induced by source paper "team nimbro at mbzirc 2017 autonomous valve stem turning using a wrench"):
  with members:
    - "rgb d object detection and semantic segmentation for autonomous manipulation in clutter"
    - "densecap fully convolutional localization networks for dense captioning"
    - "fast r cnn"

Connected through hyperedge HE-4 (induced by source paper "team nimbro at mbzirc 2017 fast landing on a moving target and treasure hunting with a team of mavs"):
  with members:
    - "fast autonomous flight in warehouses for inventory applications"
    - "a decentralized multi agent unmanned aerial system to search pick up and relocate objects"
    - "the eth mav team in the mbz international robotics challenge"

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)