human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "closed chain manipulation of large objects by multi arm robotic systems"
  Abstract: Closed kinematic chains are created whenever multiple robot arms concurrently manipulate a single object. The closed-chain constraint, when coupled with robot joint limits, dramatically changes the connectivity of the configuration space. We propose a regrasping move, termed “IK-switch,” which allows efficiently bridging components of the configuration space that are otherwise mutually disconnected. This move, combined with several other developments, such as a method to stabilize the manipulated object using the environment, a new tree structure, and a compliant control scheme, enables us to address complex closed-chain manipulation tasks, such as flipping a chair frame, which is otherwise impossible to realize using existing multi-arm planning methods.

Connected through hyperedge HE-1 (induced by source paper "dual arm in hand manipulation and regrasping using dexterous manipulation graphs"):
  with members:
    - "learning dexterous in hand manipulation"
    - "dexterous manipulation graphs"
    - "pneumatic shape shifting fingers to reorient and grasp"
    - "in hand manipulation via motion cones"
    - "preparatory manipulation planning using automatically determined single and dual arms"
    - "reinforcement learning for pivoting task"
    - "developing and comparing single arm and dual arm regrasp"
    - "data driven grasp synthesis a survey"

Connected through hyperedge HE-2 (induced by source paper "designing a mechanical tool for robots with two finger parallel grippers"):
  with members:
    - "a double jaw hand designed for multi object assembly"
    - "a hand combining two simple grippers to pick up and arrange objects for assembly"
    - "arm manipulation planning of tethered tools with the help of a tool balancer"
    - "a certified complete bimanual manipulation planner"
    - "manipulation planning under changing external forces"
    - "teaching robots to do object assembly using multi modal 3d vision"

Connected through hyperedge HE-3 (induced by source paper "object placement planning and optimization for robot manipulators"):
  with members:
    - "ffrob leveraging symbolic planning for efficient task and motion planning"
    - "a certified complete bimanual manipulation planner"
    - "data driven grasp synthesis a survey"
    - "learning to place new objects in a scene"

Connected through hyperedge HE-4 (induced by source paper "printing while moving a new paradigm for large scale robotic 3d printing"):
  with members:
    - "mobile robotic fabrication at 1 1 scale the in situ fabricator"
    - "robotsp a fast solution to the robotic task sequencing problem"
    - "introducing slambench a performance and accuracy benchmarking methodology for slam"

Connected through hyperedge HE-5 (induced by source paper "dexterous manipulation graphs"):
  with members:
    - "sampling based planning of in hand manipulation with external pushes"

Connected through hyperedge HE-6 (induced by source paper "preparatory manipulation planning using automatically determined single and dual arms"):
  with members:
    - "developing and comparing single arm and dual arm regrasp"

Connected through hyperedge HE-7 (induced by source paper "a certified complete bimanual manipulation planner"):
  with members:
    - "developing and comparing single arm and dual arm regrasp"
    - "completeness of randomized kinodynamic planners with state based steering"
    - "analyzing the utility of a support pin in sequential robotic manipulation"
    - "a single query manipulation planner"
    - "a general fast and robust implementation of the time optimal path parameterization algorithm"
    - "sampling based algorithms for optimal motion planning"

Question: Please tell me which class the center node 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)