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: "safe aggressive quadrotor flight via reachability based trajectory design"
  Abstract: Quadrotors can provide services such as infrastructure inspection and search-and-rescue, which require operating autonomously in cluttered environments. Autonomy is typically achieved with receding-horizon planning, where a short plan is executed while a new one is computed, because sensors receive limited information at any time. To ensure safety and prevent robot loss, plans must be verified as collision free despite uncertainty (e.g, tracking error). Existing spline-based planners dilate obstacles uniformly to compensate for uncertainty, which can be conservative. On the other hand, reachability-based planners can include trajectory-dependent uncertainty as a function of the planned trajectory. This work applies Reachability-based Trajectory Design (RTD) to plan quadrotor trajectories that are safe despite trajectory-dependent tracking error. This is achieved by using zonotopes in a novel way for online planning. Simulations show aggressive flight up to 5 m/s with zero crashes in 500 cluttered, randomized environments.

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"
    - "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"
    - "reducing the barrier to entry of complex robotic software a moveit case study"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-2 (induced by source paper "towards scalable continuous time trajectory optimization for multi robot navigation"):
  with members:
    - "trajectory generation for multiagent point to point transitions via distributed model predictive control"
    - "online trajectory generation with distributed model predictive control for multi robot motion planning"
    - "continuous time trajectory optimization for decentralized multi robot navigation"
    - "safe certificate based maneuvers for teams of quadrotors using differential flatness"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"
    - "an effective algorithmic framework for near optimal multi robot path planning"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"

Connected through hyperedge HE-3 (induced by source paper "leveraging the template and anchor framework for safe online robotic gait design"):
  with members:
    - "walking with confidence safety regulation for full order biped models"
    - "safe adaptive switching among dynamical movement primitives application to 3d limit cycle walkers"
    - "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"

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)