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: "feedback mpc for torque controlled legged robots"
  Abstract: The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynamic systems such as legged robots. This problem is commonly circumvented by using a fast tracking controller to compensate for model errors between updates. In this work, we show that the feedback policy from a Differential Dynamic Programming (DDP) based MPC algorithm is a viable alternative to bridge the gap between the low MPC update rate and the actuation command rate. We propose to augment the DDP approach with a relaxed barrier function to address inequality constraints arising from the friction cone. A frequency-dependent cost function is used to reduce the sensitivity to high-frequency model errors and actuator bandwidth limits. We demonstrate that our approach can find stable locomotion policies for the torque-controlled quadruped, ANYmal, both in simulation and on hardware.

Connected through hyperedge HE-1 (induced by source paper "mpc net a first principles guided policy search"):
  with members:
    - "data efficient reinforcement learning for legged robots"
    - "iterative reinforcement learning based design of dynamic locomotion skills for cassie"
    - "on the convergence of adam and beyond"
    - "learning agile and dynamic motor skills for legged robots"
    - "policies modulating trajectory generators"
    - "an algorithmic perspective on imitation learning"
    - "sim to real learning agile locomotion for quadruped robots"
    - "learning to walk via deep reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "whole body mpc for a dynamically stable mobile manipulator"):
  with members:
    - "frequency aware model predictive control"
    - "hierarchical optimization for whole body control of wheeled inverted pendulum humanoids"
    - "a whole body model predictive control scheme including external contact forces and com height variations"
    - "a mpc walking framework with external contact forces"
    - "real time motion planning of legged robots a model predictive control approach"
    - "an efficient optimal planning and control framework for quadrupedal locomotion"
    - "automatic differentiation of rigid body dynamics for optimal control and estimation"

Connected through hyperedge HE-3 (induced by source paper "rolling in the deep hybrid locomotion for wheeled legged robots using online trajectory optimization"):
  with members:
    - "fast and continuous foothold adaptation for dynamic locomotion through cnns"
    - "planning hybrid driving stepping locomotion on multiple levels of abstraction"
    - "keep rollin whole body motion control and planning for wheeled quadrupedal robots"
    - "efficient kinematic planning for mobile manipulators with non holonomic constraints using optimal control"

Connected through hyperedge HE-4 (induced by source paper "sensitivity of legged balance control to uncertainties and sampling period"):
  with members:
    - "stair climbing stabilization of the hrp 4 humanoid robot using whole body admittance control"

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)