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 "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.

Includes members:
  Member "application of wrench based feasibility analysis to the online trajectory optimization of legged robots":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimizing dynamic trajectories for robustness to disturbances using polytopic projections")
  Member "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "whole body walking generation using contact parametrization a non linear trajectory optimization approach")
  Member "motion planning for quadrupedal locomotion coupled planning terrain mapping and whole body control":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crocoddyl an efficient and versatile framework for multi contact optimal control")
  Member "planning and execution of dynamic whole body locomotion for a hydraulic quadruped on challenging terrain":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning how to walk warm starting optimal control solver with memory of motion")
  Member "on line and on board planning and perception for quadrupedal locomotion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast and continuous foothold adaptation for dynamic locomotion through cnns")

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)