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: "frequency aware model predictive control"
  Abstract: Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic tasks, the presence of unmodeled dynamics renders the motion infeasible on the real system. Model errors cannot be only a result of model simplifications, but also naturally arise when deploying the robot in unstructured and nondeterministic environments. Predominantly, compliant contacts and actuator dynamics lead to bandwidth limitations. While classical control methods provide tools to synthesize controllers that are robust to a class of model errors, such a notion is missing in modern trajectory optimization, which is solved in the time domain. We propose frequency-shaped cost functions to achieve robust solutions in the context of optimal control for legged robots. Through simulation and hardware experiments we show that motion plans can be made compatible with bandwidth limits set by actuators and contact dynamics. The smoothness of the model predictive solutions can be continuously tuned without compromising the feasibility of the problem. Experiments with the quadrupedal robot ANYmal, which is driven by highly compliant series elastic actuators, showed significantly improved tracking performance of the planned motion, torque, and force trajectories and enabled the machine to walk robustly on terrain with unmodeled compliance.

Connected through hyperedge HE-1 (induced by source paper "stance locomotion adaptation over soft terrain"):
  with members:
    - "heuristic planning for rough terrain locomotion in presence of external disturbances and variable perception quality"
    - "dynamic locomotion for passive ankle biped robots and humanoids using whole body locomotion control"
    - "passive whole body control for quadruped robots experimental validation over challenging terrain"
    - "contact implicit optimization of locomotion trajectories for a quadrupedal microrobot"
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "robust whole body motion control of legged robots"
    - "robot impedance control and passivity analysis with inner torque and velocity feedback loops"
    - "momentum control with hierarchical inverse dynamics on a torque controlled humanoid"

Connected through hyperedge HE-2 (induced by source paper "whole body mpc for a dynamically stable mobile manipulator"):
  with members:
    - "feedback mpc for torque controlled legged robots"
    - "hierarchical optimization for whole body control of wheeled inverted pendulum humanoids"
    - "a whole body model predictive control scheme including external contact forces and com height variations"
    - "a mpc walking framework with external contact forces"
    - "real time motion planning of legged robots a model predictive control approach"
    - "an efficient optimal planning and control framework for quadrupedal locomotion"
    - "automatic differentiation of rigid body dynamics for optimal control and estimation"

Connected through hyperedge HE-3 (induced by source paper "feedback mpc for torque controlled legged robots"):
  with members:
    - "sensitivity of legged balance control to uncertainties and sampling period"
    - "real time motion planning of legged robots a model predictive control approach"
    - "an efficient optimal planning and control framework for quadrupedal locomotion"
    - "robot impedance control and passivity analysis with inner torque and velocity feedback loops"
    - "balancing and walking using full dynamics lqr control with contact constraints"

Connected through hyperedge HE-4 (induced by source paper "highly dynamic quadruped locomotion via whole body impulse control and model predictive control"):
  with members:
    - "dynamic locomotion for passive ankle biped robots and humanoids using whole body locomotion control"
    - "learning agile and dynamic motor skills for legged robots"
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "stability of surface contacts for humanoid robots closed form formulae of the contact wrench cone for rectangular support areas"

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)