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 "an embodied platform invariant architecture for connecting high level spatial commands to platform articulation"):
  Abstract: In contexts such as teleoperation, robot reprogramming, human-robot-interaction, and neural prosthetics, conveying movement commands to a robotic platform is often a limiting factor. Currently, many applications rely on joint-angle-by-joint-angle prescriptions. This inherently requires a large number of parameters to be specified by the user that scales with the number of degrees of freedom on a platform, creating high bandwidth requirements for interfaces. This paper presents an efficient representation of high-level, spatial commands that specifies many joint angles with relatively few parameters based on a spatial architecture that is judged favorably by human viewers. In particular, a general method for labeling connected platform linkages, generating a databank of user-specified poses, and mapping between high-level spatial commands and specific platform static configurations are presented. Thus, this architecture is ``platform-invariant'' where the same high-level, spatial command can be executed on any platform. This has the advantage that our commands have meaning for human movers as well. In order to achieve this, we draw inspiration from Laban/Bartenieff Movement Studies, an embodied taxonomy for movement description. The architecture is demonstrated through implementation on 26 spatial directions for a Rethink Robotics Baxter, an Aldebaran NAO, and a KUKA youBot. User studies are conducted to validate the claims of the proposed framework.

Includes members:
  Member "data driven grasp synthesis a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dgcm net dense geometrical correspondence matching network for incremental experience based robotic grasping")
  Member "the nao humanoid a combination of performance and affordability":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on human robot interaction using multiple modes")

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)