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: "a benchmarking of dcm based architectures for position and velocity controlled walking of humanoid robots"
  Abstract: This paper contributes towards the development and comparison of Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot locomotion. More precisely, we present and compare several DCM based implementations of a three layer control architecture. From top to bottom, these three layers are here called: trajectory optimization, simplified model control, and whole-body QP control. All layers use the DCM concept to generate references for the layer below. For the simplified model control layer, we present and compare both instantaneous and Receding Horizon Control controllers. For the whole-body QP control layer, we present and compare controllers for position and velocity control robots. Experimental results are carried out on the one-meter tall iCub humanoid robot. We show which implementation of the above control architecture allows the robot to achieve a walking velocity of 0.41 meters per second.

Connected through hyperedge HE-1 (induced by source paper "whole body walking generation using contact parametrization a non linear trajectory optimization approach"):
  with members:
    - "a control architecture with online predictive planning for position and torque controlled walking of humanoid robots"
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization"
    - "real time motion planning of legged robots a model predictive control approach"
    - "straight leg walking through underconstrained whole body control"
    - "a receding horizon push recovery strategy for balancing the icub humanoid robot"
    - "when to make a step tackling the timing problem in multi contact locomotion by topp mpc"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-2 (induced by source paper "online dcm trajectory generation for push recovery of torque controlled humanoid robots"):
  with members:
    - "walking stabilization using step timing and location adjustment on the humanoid robot atlas"
    - "robust bipedal locomotion control based on model predictive control and divergent component of motion"
    - "step timing adjustment a step toward generating robust gaits"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-3 (induced by source paper "whole body geometric retargeting for humanoid robots"):
  with members:
    - "telexistence and teleoperation for walking humanoid robots"
    - "deepmimic example guided deep reinforcement learning of physics based character skills"
    - "balancing experiments on a torque controlled humanoid with hierarchical inverse dynamics"

Connected through hyperedge HE-4 (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"
    - "robust bipedal locomotion control based on model predictive control and divergent component of motion"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-5 (induced by source paper "telexistence and teleoperation for walking humanoid robots"):
  with members:
    - "a control architecture with online predictive planning for position and torque controlled walking of humanoid robots"
    - "a whole body software abstraction layer for control design of free floating mechanical systems"
    - "a review paper on oculus rift a virtual reality headset"

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)