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 "learning postural synergies for categorical grasping through shape space registration"):
  Abstract: Every time a person encounters an object with a given degree of familiarity, he/she immediately knows how to grasp it. Adaptation of the movement of the hand according to the object geometry happens effortlessly because of the accumulated knowledge of previous experiences grasping similar objects. In this paper, we present a novel method for inferring grasp configurations based on the object shape. Grasping knowledge is gathered in a synergy space of the robotic hand built by following a human grasping taxonomy. The synergy space is constructed through human demonstrations employing a exoskeleton that provides force feedback, which provides the advantage of evaluating the quality of the grasp. The shape descriptor is obtained by means of a categorical non-rigid registration that encodes typical intra-class variations. This approach is especially suitable for on-line scenarios where only a portion of the object's surface is observable. This method is demonstrated through simulation and real robot experiments by grasping objects never seen before by the robot.

Includes members:
  Member "transferring category based functional grasping skills by latent space non rigid registration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "autonomous bimanual functional regrasping of novel object class instances")
  Member "supervised autonomous locomotion and manipulation for disaster response with a centaur like robot":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "value iteration networks on multiple levels of abstraction")
  Member "autonomous dual arm manipulation of familiar objects":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "autonomous bimanual functional regrasping of novel object class instances")
  Member "transferring grasping skills to novel instances by latent space non rigid registration":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "kpam keypoint affordances for category level robotic manipulation")
  Member "compact part based shape spaces for dense correspondences":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transferring category based functional grasping skills by latent space non rigid registration")
  Member "point set registration coherent point drift":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "3d point cloud processing and learning for autonomous driving")

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)