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: "reducing the barrier to entry of complex robotic software a moveit case study"
  Abstract: Developing robot agnostic software frameworks involves synthesizing the disparate fields of robotic theory and software engineering while simultaneously accounting for a large variability in hardware designs and control paradigms. As the capabilities of robotic software frameworks increase, the setup difficulty and learning curve for new users also increase. If the entry barriers for configuring and using the software on robots is too high, even the most powerful of frameworks are useless. A growing need exists in robotic software engineering to aid users in getting started with, and customizing, the software framework as necessary for particular robotic applications. In this paper a case study is presented for the best practices found for lowering the barrier of entry in the MoveIt! framework, an open-source tool for mobile manipulation in ROS, that allows users to 1) quickly get basic motion planning functionality with minimal initial setup, 2) automate its configuration and optimization, and 3) easily customize its components. A graphical interface that assists the user in configuring MoveIt! is the cornerstone of our approach, coupled with the use of an existing standardized robot model for input, automatically generated robot-specific configuration files, and a plugin-based architecture for extensibility. These best practices are summarized into a set of barrier to entry design principles applicable to other robotic software. The approaches for lowering the entry barrier are evaluated by usage statistics, a user survey, and compared against our design objectives for their effectiveness to users.

Connected through hyperedge HE-1 (induced by source paper "reachable sets for safe real time manipulator trajectory design"):
  with members:
    - "towards provably not at fault control of autonomous robots in arbitrary dynamic environments"
    - "safe aggressive quadrotor flight via reachability based trajectory design"
    - "bridging the gap between safety and real time performance in receding horizon trajectory design for mobile robots"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "funnel libraries for real time robust feedback motion planning"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-2 (induced by source paper "robot calligraphy using pseudospectral optimal control in conjunction with a novel dynamic brush model"):
  with members:
    - "steap simultaneous trajectory estimation and planning"

Connected through hyperedge HE-3 (induced by source paper "safe physical hri toward a unified treatment of speed and separation monitoring together with power and force limiting"):
  with members:
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "compact real time avoidance on a humanoid robot for human robot interaction"
    - "toward safe separation distance monitoring from rgb d sensors in human robot interaction"
    - "densepose dense human pose estimation in the wild"
    - "deepercut a deeper stronger and faster multi person pose estimation model"
    - "realtime multi person 2d pose estimation using part affinity fields"

Connected through hyperedge HE-4 (induced by source paper "solving service robot tasks ut austin villa home 2019 team report"):
  with members:
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "multimodal feedback for active robot object interaction"
    - "laair a layered architecture for autonomous interactive robots"
    - "yolo9000 better faster stronger"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-5 (induced by source paper "robust and fast generation of top and side grasps for unknown objects"):
  with members:
    - "hypothesis based belief planning for dexterous grasping"
    - "a novel geometry based algorithm for robust grasping in extreme clutter environment"
    - "dex net 2 0 deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics"
    - "deep learning for detecting robotic grasps"

Connected through hyperedge HE-6 (induced by source paper "improving grasp performance using in hand proximity and contact sensing"):
  with members:
    - "morphological and embedded computation in a self contained soft robotic hand"
    - "benchmarking in manipulation research using the yale cmu berkeley object and model set"

Connected through hyperedge HE-7 (induced by source paper "sparser sparse roadmaps"):
  with members:
    - "experience based planning with sparse roadmap spanners"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-8 (induced by source paper "analysis and observations from the first amazon picking challenge"):
  with members:
    - "a dataset for improved rgbd based object detection and pose estimation for warehouse pick and place"
    - "simultaneous detection and segmentation"

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)