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: "robust bipedal locomotion control based on model predictive control and divergent component of motion"
  Abstract: In this paper, previous works on the Model Predictive Control (MPC) and the Divergent Component of Motion (DCM) for bipedal walking control are extended. To this end, we employ a single MPC which uses a combination of Center of Pressure (CoP) manipulation, step adjustment, and Centroidal Moment Pivot (CMP) modulation to design a robust walking controller. Furthermore, we exploit the concept of time-varying DCM to generalize our walking controller for walking in uneven surfaces. Using our scheme, a general and robust walking controller is designed which can be implemented on robots with different control authorities, for walking on various environments, e.g. uneven terrains or surfaces with a very limited feasible area for stepping. The effectiveness of the proposed approach is verified through simulations on different scenarios and comparison to the state of the art.

Connected through hyperedge HE-1 (induced by source paper "online dcm trajectory generation for push recovery of torque controlled humanoid robots"):
  with members:
    - "a benchmarking of dcm based architectures for position and velocity controlled walking of humanoid robots"
    - "walking stabilization using step timing and location adjustment on the humanoid robot atlas"
    - "step timing adjustment a step toward generating robust gaits"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-2 (induced by source paper "nonlinear model predictive control for robust bipedal locomotion exploring com height and angular momentum changes"):
  with members:
    - "a whole body model predictive control scheme including external contact forces and com height variations"
    - "on time optimisation of centroidal momentum dynamics"
    - "robust optimal planning and control of non periodic bipedal locomotion with a centroidal momentum model"
    - "dynamic walking over rough terrains by nonlinear predictive control of the floating base inverted pendulum"

Connected through hyperedge HE-3 (induced by source paper "a benchmarking of dcm based architectures for position velocity and torque controlled humanoid robots"):
  with members:
    - "online dcm trajectory generation for push recovery of torque controlled humanoid robots"
    - "a benchmarking of dcm based architectures for position and velocity controlled walking of humanoid robots"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-4 (induced by source paper "a hierarchical framework to generate robust biped locomotion based on divergent component of motion"):
  with members:
    - "step timing adjustment a step toward generating robust gaits"

Connected through hyperedge HE-5 (induced by source paper "a robust biped locomotion based on linear quadratic gaussian controller and divergent component of motion"):
  with members:
    - "stepping stabilization using a combination of dcm tracking and step adjustment"

Connected through hyperedge HE-6 (induced by source paper "a reactive and efficient walking pattern generator for robust bipedal locomotion"):
  with members:
    - "walking stabilization using step timing and location adjustment on the humanoid robot atlas"
    - "pattern generation for walking on slippery terrains"
    - "a robust walking controller based on online step location and duration optimization for bipedal locomotion"
    - "push recovery of a humanoid robot based on model predictive control and capture point"
    - "step timing adjustment a step toward generating robust gaits"
    - "stepping stabilization using a combination of dcm tracking and step adjustment"

Connected through hyperedge HE-7 (induced by source paper "push recovery of a position controlled humanoid robot based on capture point feedback control"):
  with members:
    - "push recovery of a humanoid robot based on model predictive control and capture point"
    - "step timing adjustment a step toward generating robust gaits"

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)