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: "a versatile framework for robust and adaptive door operation with a mobile manipulator robot"
  Abstract: The ability to deal with articulated objects is very important for robots assisting humans. In this work a general framework for the robust operation of different types of doors using an autonomous robotic mobile manipulator is proposed. To push the state-of-the-art in robustness and speed performance, we devise a novel algorithm that fuses a convolutional neural network with efficient point cloud processing. This advancement allows for real-time grasping pose estimation of single or multiple handles from RGB-D images, providing a speed up for assistive human-centered behaviors. In addition, we propose a versatile Bayesian framework that endows the robot with the ability to infer the door kinematic model from observations of its motion while opening it and learn from previous experiences or human demonstrations. Combining this probabilistic approach with a state-of-the-art motion planner, we achieve efficient door grasping and subsequent door operation regardless of the kinematic model using the Toyota Human Support Robot.

Connected through hyperedge HE-1 (induced by source paper "finding locomanipulation plans quickly in the locomotion constrained manifold"):
  with members:
    - "thermal recovery of multi limbed robots with electric actuators"
    - "efficient humanoid contact planning using learned centroidal dynamics prediction"
    - "a whole body pose taxonomy for loco manipulation tasks"

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)