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 "robust and fast generation of top and side grasps for unknown objects"):
  Abstract: In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camera, and of selecting the most promising one. We demonstrate the effectiveness of our approach on a picking scenario on a real robot platform. Our approach has shown to be more reliable than another recent geometry-based method considered as baseline [7] in terms of grasp stability, by increasing the successful grasp attempts by a factor of six.

Includes members:
  Member "hypothesis based belief planning for dexterous grasping":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "grasping and manipulation with a multi fingered hand")
  Member "a novel geometry based algorithm for robust grasping in extreme clutter environment":
    also connected through other hyperedges:
      (none)
  Member "dex net 2 0 deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning pregrasp manipulation of objects from ungraspable poses")
  Member "reducing the barrier to entry of complex robotic software a moveit case study":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reachable sets for safe real time manipulator trajectory design")
  Member "deep learning for detecting robotic grasps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the state of service robots current bottlenecks in object perception and manipulation")

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)