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: "nonlinear model predictive control for multi micro aerial vehicle robust collision avoidance"
  Abstract: Multiple multirotor Micro Aerial Vehicles sharing the same airspace require a reliable and robust collision avoidance technique. In this paper we address the problem of multi-MAV reactive collision avoidance. A model-based controller is employed to achieve simultaneously reference trajectory tracking and collision avoidance. Moreover, we also account for the uncertainty of the state estimator and the other agents position and velocity uncertainties to achieve a higher degree of robustness. The proposed approach is decentralized, does not require collision-free reference trajectory and accounts for the full MAV dynamics. We validated our approach in simulation and experimentally.

Connected through hyperedge HE-1 (induced by source paper "a complete system for vision based micro aerial vehicle mapping planning and flight in cluttered environments"):
  with members:
    - "maplab an open framework for research in visual inertial mapping and localization"
    - "safe local exploration for replanning in cluttered unknown environments for microaerial vehicles"
    - "fast autonomous flight in gps denied and cluttered environments"
    - "vins mono a robust and versatile monocular visual inertial state estimator"
    - "sparse 3d topological graphs for micro aerial vehicle planning"
    - "c blox a scalable and consistent tsdf based dense mapping approach"
    - "real time trajectory replanning for mavs using uniform b splines and a 3d circular buffer"
    - "voxblox incremental 3d euclidean signed distance fields for on board mav planning"

Connected through hyperedge HE-2 (induced by source paper "the eth mav team in the mbz international robotics challenge"):
  with members:
    - "a decentralized multi agent unmanned aerial system to search pick up and relocate objects"
    - "robust collaborative object transportation using multiple mavs"
    - "aerial picking and delivery of magnetic objects with mavs"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"

Connected through hyperedge HE-3 (induced by source paper "a decentralized multi agent unmanned aerial system to search pick up and relocate objects"):
  with members:
    - "aerial picking and delivery of magnetic objects with mavs"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"

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)