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: "network of nano landers for in situ characterization of asteroid impact studies"
  Abstract: Exploration of asteroids and comets can give insight into the origins of the solar system and can be instrumental in planetary defence and in-situ resource utilization (ISRU). Asteroids, due to their low gravity are a challenging target for surface exploration. Current missions envision performing touch-and-go operations over an asteroid surface. In this work, we analyse the feasibility of sending scores of nano-landers, each 1 kg in mass and volume of 1U, or 1000 cm3. These landers would hop, roll and fly over the asteroid surface. The landers would include science instruments such as stereo cameras, hand-lens imagers and spectrometers to characterize rock composition. A network of nano-landers situated on the surface of an asteroid can provide unique and very detailed measurements of a spacecraft impacting onto an asteroid surface. A full-scale, artificial impact experiment onto an asteroid can help characterize its composition and geology and help in the development of asteroid deflection techniques intended for planetary defence. Scores of nano-landers could provide multiple complementary views of the impact, resultant seismic activity and trajectory of the ejecta. The nano-landers can analyse the pristine, unearthed regolith shielded from effects of UV and cosmic rays and that may be millions of years old. Our approach to formulating this mission concepts utilizes automated machine learning techniques in the planning and design of space systems. We use a form of Darwinian selection to select and identify suitable number of nano-landers, the on-board instruments and control system to explore and navigate the asteroid environment. Scenarios are generated in simulation and evaluated against quantifiable mission goals such as area explored on the asteroid and amount of data recorded from the impact event.

Connected through hyperedge HE-1 (induced by source paper "planning and navigation of climbing robots in low gravity environments"):
  with members:
    - "guidance navigation and control of multirobot systems in cooperative cliff climbing"
    - "multirobot cliff climbing on low gravity environments"
    - "autonomous multirobot excavation for lunar applications"

Connected through hyperedge HE-2 (induced by source paper "mobility and science operations on an asteroid using a hopping small spacecraft on stilts"):
  with members:
    - "spherical planetary robot for rugged terrain traversal"

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)