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 "online replanning in belief space for partially observable task and motion problems"):
  Abstract: To solve multi-step manipulation tasks in the real world, an autonomous robot must take actions to observe its environment and react to unexpected observations. This may require opening a drawer to observe its contents or moving an object out of the way to examine the space behind it. If the robot fails to detect an important object, it must update its belief about the world and compute a new plan of action. Additionally, a robot that acts noisily will never exactly arrive at a desired state. Still, it is important that the robot adjusts accordingly in order to keep making progress towards achieving the goal. In this work, we present an online planning and execution system for robots faced with these kinds of challenges. Our approach is able to efficiently solve partially observable problems both in simulation and in a real-world kitchen.

Includes members:
  Member "deepim deep iterative matching for 6d pose estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "neural mesh refiner for 6 dof pose estimation")
  Member "representing robot task plans as robust logical dynamical systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "transferable task execution from pixels through deep planning domain learning")
  Member "bounded policy synthesis for pomdps with safe reachability objectives":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "sampling based methods for factored task and motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reactive navigation in partially familiar planar environments using semantic perceptual feedback")
  Member "stripstream integrating symbolic planners and blackbox samplers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transferable task execution from pixels through deep planning domain learning")
  Member "an anytime algorithm for task and motion mdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hybrid planning for dynamic multimodal stochastic shortest paths")
  Member "ffrob leveraging symbolic planning for efficient task and motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep compositional robotic planners that follow natural language commands")
  Member "posecnn a convolutional neural network for 6d object pose estimation in cluttered scenes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "neural mesh refiner for 6 dof pose estimation")

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)