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 "a vision guided multi robot cooperation framework for learning by demonstration and task reproduction"):
  Abstract: This paper presents a vision-based learning-by-demonstration approach to enable robots to learn and complete a manipulation task cooperatively. With this method, a vision system is involved in both the task demonstration and reproduction stages. An expert first demonstrates how to use tools to perform a task, while the tool motion is observed using a vision system. The demonstrations are then encoded using a statistical model to generate a reference motion trajectory. Equipped with the same tools and the learned model, the robot is guided by vision to reproduce the task. The task performance was evaluated in terms of both accuracy and speed. However, simply increasing the robot's speed could decrease the reproduction accuracy. To this end, a dual-rate Kalman filter is employed to compensate for latency between the robot and vision system. More importantly, the sampling rates of the reference trajectory and the robot speed are optimised adaptively according to the learned motion model. We demonstrate the effectiveness of our approach by performing two tasks: a trajectory reproduction task and a bimanual sewing task. We show that using our vision-based approach, the robots can conduct effective learning by demonstrations and perform accurate and fast task reproduction. The proposed approach is generalisable to other manipulation tasks, where bimanual or multi-robot cooperation is required.

Includes members:
  Member "autonomous scanning for endomicroscopic mosaicing and 3d fusion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "intraoperative robotic assisted large area high speed microscopic imaging and intervention")
  Member "real time 3d tracking of articulated tools for robotic surgery":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "super deep a surgical perception framework for robotic tissue manipulation using deep learning for feature extraction")

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)