human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "biped stabilization by linear feedback of the variable height inverted pendulum model"):
  Abstract: The variable-height inverted pendulum (VHIP) model enables a new balancing strategy, based on vertical motions of the center of mass, in addition to the well-known ankle strategy. We propose a biped stabilizer based on linear feedback of the VHIP that is simple to implement, coincides with the state-of-the-art for small perturbations and is able to recover from larger perturbations thanks to this new strategy. This solution is based on "best-effort" pole placement of the 4D divergent component of motion of the VHIP under input feasibility and state viability constraints. We complement it with a suitable whole-body admittance control law and test the stabilizer on the HRP-4 humanoid robot.

Includes members:
  Member "stair climbing stabilization of the hrp 4 humanoid robot using whole body admittance control":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "data efficient and safe learning for locomotion via simplified model")
  Member "capturability based pattern generation for walking with variable height":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust humanoid contact planning with learned zero and one step capturability prediction")
  Member "dynamic walking over rough terrains by nonlinear predictive control of the floating base inverted pendulum":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "feasible region an actuation aware extension of the support region")
  Member "walking on partial footholds including line contacts with the humanoid robot atlas":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stair climbing stabilization of the hrp 4 humanoid robot using whole body admittance control")
  Member "multi contact walking pattern generation based on model preview control of 3d com accelerations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "formal connections between template and anchor models via approximate simulation")
  Member "zmp support areas for multi contact mobility under frictional constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reactive task and motion planning for robust whole body dynamic locomotion in constrained environments")

Question: Please tell me which class the source paper 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)