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 "online dcm trajectory generation for push recovery of torque controlled humanoid robots"):
  Abstract: We present a computationally efficient method for online planning of bipedal walking trajectories with push recovery. In particular, the proposed methodology fits control architectures where the Divergent-Component-of-Motion (DCM) is planned beforehand, and adds a step adapter to adjust the planned trajectories and achieve push recovery. Assuming that the robot is in a single support state, the step adapter generates new positions and timings for the next step. The step adapter is active in single support phases only, but the proposed torque-control architecture considers double support phases too. The key idea for the design of the step adapter is to impose both initial and final DCM step values using an exponential interpolation of the time varying ZMP trajectory.This allows us to cast the push recovery problem as a Quadratic Programming (QP) one, and to solve it online with state-of-the-art optimisers. The overall approach is validated with simulations of the torque-controlled 33 kg humanoid robot iCub. Results show that the proposed strategy prevents the humanoid robot from falling while walking at 0.28 m/s and pushed with external forces up to 150 Newton for 0.05 seconds.

Includes members:
  Member "a benchmarking of dcm based architectures for position and velocity controlled walking of humanoid robots":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "whole body walking generation using contact parametrization a non linear trajectory optimization approach")
  Member "walking stabilization using step timing and location adjustment on the humanoid robot atlas":
    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 "robust bipedal locomotion control based on model predictive control and divergent component of motion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "nonlinear model predictive control for robust bipedal locomotion exploring com height and angular momentum changes")
  Member "step timing adjustment a step toward generating robust gaits":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust humanoid contact planning with learned zero and one step capturability prediction")
  Member "trajectory generation for multi contact momentum control":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "whole body walking generation using contact parametrization a non linear trajectory optimization approach")

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)