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 "a reactive and efficient walking pattern generator for robust bipedal locomotion"):
  Abstract: Available possibilities to prevent a biped robot from falling down in the presence of severe disturbances are mainly Center of Pressure (CoP) modulation, step location and timing adjustment, and angular momentum regulation. In this paper, we aim at designing a walking pattern generator which employs an optimal combination of these tools to generate robust gaits. In this approach, first, the next step location and timing are decided consistent with the commanded walking velocity and based on the Divergent Component of Motion (DCM) measurement. This stage which is done by a very small-size Quadratic Program (QP) uses the Linear Inverted Pendulum Model (LIPM) dynamics to adapt the switching contact location and time. Then, consistent with the first stage, the LIPM with flywheel dynamics is used to regenerate the DCM and angular momentum trajectories at each control cycle. This is done by modulating the CoP and Centroidal Momentum Pivot (CMP) to realize a desired DCM at the end of current step. Simulation results show the merit of this reactive approach in generating robust and dynamically consistent walking patterns.

Includes members:
  Member "walking stabilization using step timing and location adjustment on the humanoid robot atlas":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust humanoid contact planning with learned zero and one step capturability prediction")
  Member "pattern generation for walking on slippery terrains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust humanoid locomotion using trajectory optimization and sample efficient learning")
  Member "a robust walking controller based on online step location and duration optimization for bipedal locomotion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a whole body model predictive control scheme including external contact forces and com height variations")
  Member "robust bipedal locomotion control based on model predictive control and divergent component of motion":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "online dcm trajectory generation for push recovery of torque controlled humanoid robots")
  Member "push recovery of a humanoid robot based on model predictive control and capture point":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust bipedal locomotion control based on model predictive control and divergent component of motion")
  Member "step timing adjustment a step toward generating robust gaits":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust humanoid contact planning with learned zero and one step capturability prediction")
  Member "stepping stabilization using a combination of dcm tracking and step adjustment":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a robust biped locomotion based on linear quadratic gaussian controller and divergent component of motion")

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)