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: "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"
  Abstract: Precise trajectory tracking is a crucial property for \acp{MAV} to operate in cluttered environment or under disturbances. In this paper we present a detailed comparison between two state-of-the-art model-based control techniques for \ac{MAV} trajectory tracking. A classical \ac{LMPC} is presented and compared against a more advanced \ac{NMPC} that considers the full system model. In a careful analysis we show the advantages and disadvantages of the two implementations in terms of speed and tracking performance. This is achieved by evaluating hovering performance, step response, and aggressive trajectory tracking under nominal conditions and under external wind disturbances.

Connected through hyperedge HE-1 (induced by source paper "airsim drone racing lab"):
  with members:
    - "deep drone racing from simulation to reality with domain randomization"
    - "flying through a narrow gap using neural network an end to end planning and control approach"
    - "event based vision a survey"
    - "flightgoggles photorealistic sensor simulation for perception driven robotics using photogrammetry and virtual reality"
    - "fiesta fast incremental euclidean distance fields for online motion planning of aerial robots"
    - "deep drone racing learning agile flight in dynamic environments"
    - "a real time game theoretic planner for autonomous two player drone racing"
    - "the blackbird dataset a large scale dataset for uav perception in aggressive flight"

Connected through hyperedge HE-2 (induced by source paper "nonlinear mpc with motor failure identification and recovery for safe and aggressive multicopter flight"):
  with members:
    - "the control toolbox an open source c library for robotics optimal and model predictive control"
    - "a family of iterative gauss newton shooting methods for nonlinear optimal control"

Connected through hyperedge HE-3 (induced by source paper "towards scalable continuous time trajectory optimization for multi robot navigation"):
  with members:
    - "trajectory generation for multiagent point to point transitions via distributed model predictive control"
    - "online trajectory generation with distributed model predictive control for multi robot motion planning"
    - "safe aggressive quadrotor flight via reachability based trajectory design"
    - "continuous time trajectory optimization for decentralized multi robot navigation"
    - "safe certificate based maneuvers for teams of quadrotors using differential flatness"
    - "an effective algorithmic framework for near optimal multi robot path planning"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"

Connected through hyperedge HE-4 (induced by source paper "nonlinear model predictive control with actuator constraints for multi rotor aerial vehicles"):
  with members:
    - "pampc perception aware model predictive control for quadrotors"
    - "matmpc a matlab based toolbox for real time nonlinear model predictive control"
    - "trajectory generation for quadrotor based systems using numerical optimal control"

Connected through hyperedge HE-5 (induced by source paper "dcad decentralized collision avoidance with dynamics constraints for agile quadrotor swarms"):
  with members:
    - "lswarm efficient collision avoidance for large swarms with coverage constraints in complex urban scenes"
    - "accurate tracking of aggressive quadrotor trajectories using incremental nonlinear dynamic inversion and differential flatness"
    - "search based motion planning for quadrotors using linear quadratic minimum time control"

Connected through hyperedge HE-6 (induced by source paper "joint vision based navigation control and obstacle avoidance for uavs in dynamic environments"):
  with members:
    - "effective target aware visual navigation for uavs"
    - "aggressive quadrotor flight through narrow gaps with onboard sensing and computing using active vision"

Connected through hyperedge HE-7 (induced by source paper "disturbance estimation and rejection for high precision multirotor position control"):
  with members:
    - "long duration autonomy for small rotorcraft uas including recharging"
    - "unscented external force and torque estimation for quadrotors"

Connected through hyperedge HE-8 (induced by source paper "nonlinear model predictive control for 3d formation of multirotor micro aerial vehicles with relative sensing in local coordinates"):
  with members:
    - "decentralized multi robot encirclement of a 3d target with guaranteed collision avoidance"

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)