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: "efficient humanoid contact planning using learned centroidal dynamics prediction"
  Abstract: Humanoid robots dynamically navigate an environment by interacting with it via contact wrenches exerted at intermittent contact poses. Therefore, it is important to consider dynamics when planning a contact sequence. Traditional contact planning approaches assume a quasi-static balance criterion to reduce the computational challenges of selecting a contact sequence over a rough terrain. This however limits the applicability of the approach when dynamic motions are required, such as when walking down a steep slope or crossing a wide gap. Recent methods overcome this limitation with the help of efficient mixed integer convex programming solvers capable of synthesizing dynamic contact sequences. Nevertheless, its exponential-time complexity limits its applicability to short time horizon contact sequences within small environments. In this paper, we go beyond current approaches by learning a prediction of the dynamic evolution of the robot centroidal momenta, which can then be used for quickly generating dynamically robust contact sequences for robots with arms and legs using a search-based contact planner. We demonstrate the efficiency and quality of the results of the proposed approach in a set of dynamically challenging scenarios.

Connected through hyperedge HE-1 (induced by source paper "accurate vision based manipulation through contact reasoning"):
  with members:
    - "let s push things forward a survey on robot pushing"
    - "combining physical simulators and object based networks for control"
    - "combining coarse and fine physics for manipulation using parallel in time integration"
    - "robustness via retrying closed loop robotic manipulation with self supervised learning"
    - "in hand manipulation via motion cones"
    - "self supervised visual planning with temporal skip connections"
    - "reactive planar manipulation with convex hybrid mpc"
    - "more than a million ways to be pushed a high fidelity experimental dataset of planar pushing"

Connected through hyperedge HE-2 (induced by source paper "robust humanoid contact planning with learned zero and one step capturability prediction"):
  with members:
    - "unified multi contact fall mitigation planning for humanoids via contact transition tree optimization"
    - "capturability based pattern generation for walking with variable height"
    - "walking stabilization using step timing and location adjustment on the humanoid robot atlas"
    - "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization"
    - "a mpc walking framework with external contact forces"
    - "structured contact force optimization for kino dynamic motion generation"
    - "step timing adjustment a step toward generating robust gaits"

Connected through hyperedge HE-3 (induced by source paper "mpc based controller with terrain insight for dynamic legged locomotion"):
  with members:
    - "fast and continuous foothold adaptation for dynamic locomotion through cnns"
    - "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"
    - "an efficient optimal planning and control framework for quadrupedal locomotion"
    - "automatic differentiation of rigid body dynamics for optimal control and estimation"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-4 (induced by source paper "on the hardware feasibility of nonlinear trajectory optimization for legged locomotion based on a simplified dynamics"):
  with members:
    - "feasible region an actuation aware extension of the support region"
    - "application of wrench based feasibility analysis to the online trajectory optimization of legged robots"
    - "passive whole body control for quadruped robots experimental validation over challenging terrain"
    - "real time motion planning of legged robots a model predictive control approach"
    - "structured contact force optimization for kino dynamic motion generation"

Connected through hyperedge HE-5 (induced by source paper "finding locomanipulation plans quickly in the locomotion constrained manifold"):
  with members:
    - "thermal recovery of multi limbed robots with electric actuators"
    - "a versatile framework for robust and adaptive door operation with a mobile manipulator robot"
    - "a whole body pose taxonomy for loco manipulation tasks"

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)