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: "heuristic planning for rough terrain locomotion in presence of external disturbances and variable perception quality"
  Abstract: The quality of visual feedback can vary significantly on a legged robot meant to traverse unknown and unstructured terrains. The map of the environment, acquired with online state-of-the-art algorithms, often degrades after a few steps, due to sensing inaccuracies, slippage and unexpected disturbances. If a locomotion algorithm is not designed to deal with this degradation, its planned trajectories might end-up to be inconsistent in reality. In this work, we propose a heuristic-based planning approach that enables a quadruped robot to successfully traverse a significantly rough terrain (e.g. stones up to 10 cm of diameter), in absence of visual feedback. When available, the approach allows also to leverage the visual feedback (e.g. to enhance the stepping strategy) in multiple ways, according to the quality of the 3D map. The proposed framework also includes reflexes, triggered in specific situations, and the possibility to estimate online an unknown time-varying disturbance and compensate for it. We demonstrate the effectiveness of the approach with experiments performed on our quadruped robot HyQ (85 kg), traversing different terrains, such as: ramps, rocks, bricks, pallets and stairs. We also demonstrate the capability to estimate and compensate for external disturbances by showing the robot walking up a ramp while pulling a cart attached to its back.

Connected through hyperedge HE-1 (induced by source paper "stance locomotion adaptation over soft terrain"):
  with members:
    - "frequency aware model predictive control"
    - "dynamic locomotion for passive ankle biped robots and humanoids using whole body locomotion control"
    - "passive whole body control for quadruped robots experimental validation over challenging terrain"
    - "contact implicit optimization of locomotion trajectories for a quadrupedal microrobot"
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "robust whole body motion control of legged robots"
    - "robot impedance control and passivity analysis with inner torque and velocity feedback loops"
    - "momentum control with hierarchical inverse dynamics on a torque controlled humanoid"

Connected through hyperedge HE-2 (induced by source paper "feasible region an actuation aware extension of the support region"):
  with members:
    - "application of wrench based feasibility analysis to the online trajectory optimization of legged robots"
    - "dynamic walking over rough terrains by nonlinear predictive control of the floating base inverted pendulum"
    - "when to make a step tackling the timing problem in multi contact locomotion by topp mpc"
    - "structured contact force optimization for kino dynamic motion generation"
    - "minkowski sum of polytopes defined by their vertices"
    - "minkowski sum of hv polytopes in rn"

Connected through hyperedge HE-3 (induced by source paper "passive whole body control for quadruped robots experimental validation over challenging terrain"):
  with members:
    - "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization"
    - "motion planning for quadrupedal locomotion coupled planning terrain mapping and whole body control"
    - "real time motion planning of legged robots a model predictive control approach"
    - "momentum control with hierarchical inverse dynamics on a torque controlled humanoid"
    - "an efficiently solvable quadratic program for stabilizing dynamic locomotion"

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)