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 "robotic tactile perception of object properties a review"):
  Abstract: Touch sensing can help robots understand their sur- rounding environment, and in particular the objects they interact with. To this end, roboticists have, in the last few decades, developed several tactile sensing solutions, extensively reported in the literature. Research into interpreting the conveyed tactile information has also started to attract increasing attention in recent years. However, a comprehensive study on this topic is yet to be reported. In an effort to collect and summarize the major scientific achievements in the area, this survey extensively reviews current trends in robot tactile perception of object properties. Available tactile sensing technologies are briefly presented before an extensive review on tactile recognition of object properties. The object properties that are targeted by this review are shape, surface material and object pose. The role of touch sensing in combination with other sensing sources is also discussed. In this review, open issues are identified and future directions for applying tactile sensing in different tasks are suggested.

Includes members:
  Member "ergodic exploration using binary sensing for nonparametric shape estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "decentralized ergodic control distribution driven sensing and exploration for multiagent systems")
  Member "connecting look and feel associating the visual and tactile properties of physical materials":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal deep learning for robot touch")
  Member "knock knock acoustic object recognition by using stacked denoising autoencoders":
    also connected through other hyperedges:
      (none)
  Member "memory unscented particle filter for 6 dof tactile localization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "in hand object pose tracking via contact feedback and gpu accelerated robotic simulation")
  Member "shape independent hardness estimation using deep learning and a gelsight tactile sensor":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "scalable tactile sensing for an omni adaptive soft robot finger")
  Member "iterative closest labeled point for tactile object shape recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "touching to see and seeing to feel robotic cross modal sensorydata generation for visual tactile perception")
  Member "localizing the object contact through matching tactile features with visual map":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "touching to see and seeing to feel robotic cross modal sensorydata generation for visual tactile perception")
  Member "deep learning for tactile understanding from visual and haptic data":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal deep learning for robot touch")

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)