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 "tactile model o fabrication and testing of a 3d printed three fingered tactile robot hand"):
  Abstract: Bringing tactile sensation to robotic hands will allow for more effective grasping, along with the wide range of benefits of human-like touch. Here we present a 3d-printed, three-fingered tactile robot hand comprising an OpenHand Model~O customized to house a TacTip optical biomimetic tactile sensor in the distal phalanx of each finger. We expect that the grasping capabilities of the Model O combined with the benefits of sophisticated tactile sensing will result in an effective platform -- the tactile Model O (T-MO). Our current T-MO design uses three JeVois machine vision systems, each comprising a miniature camera in the tactile fingertip with a vision processing module in the base of the hand. To evaluate the capabilities of the T-MO, we benchmark its grasping performance using the Gripper Assessment Benchmark on the YCB object set. We then tested its tactile sensing capabilities with two experiments: firstly, tactile object classification on a subset of objects that can be reliably grasped, and secondly, predicting whether a grasp will successfully lift one of these objects under randomly perturbed grasps that sometimes fail. In all cases, the results are consistent with the state-of-the-art, taking advantage of advances in deep learning and convolutional neural networks from computer vision that apply to the tactile image outputs. Overall, this work demonstrates that the T-MO is an effective platform for robot hand research and we expect it to open-up a range of applications in autonomous object handling. Video: this https URL

Includes members:
  Member "learning to identify object instances by touch tactile recognition via multimodal matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal deep learning for robot touch")
  Member "gelslim a high resolution compact robust and calibrated tactile sensing finger":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "contact aware controller design for complementarity systems")
  Member "in hand object stabilization by independent finger control":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "in hand object pose tracking via contact feedback and gpu accelerated robotic simulation")
  Member "from pixels to percepts highly robust edge perception and contour following using deep learning and an optical biomimetic tactile sensor":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal deep learning for robot touch")
  Member "the feeling of success does touch sensing help predict grasp outcomes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sensor fusion gated recurrent fusion to learn driving behavior from temporal multimodal data")
  Member "improved gelsight tactile sensor for measuring geometry and slip":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "omnitact a multi directional high resolution touch sensor")
  Member "benchmarking in manipulation research using the yale cmu berkeley object and model set":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "6d object pose regression via supervised learning on point clouds")
  Member "deep residual learning for image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "discrimination aware network pruning for deep model compression")

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)