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: "hybrid control trajectory optimization under uncertainty"
  Abstract: Trajectory optimization is a fundamental problem in robotics. While optimization of continuous control trajectories is well developed, many applications require both discrete and continuous, i.e., hybrid, controls. Finding an optimal sequence of hybrid controls is challenging due to the exponential explosion of discrete control combinations. Our method, based on Differential Dynamic Programming (DDP), circumvents this problem by incorporating discrete actions inside DDP: we first optimize continuous mixtures of discrete actions, and, subsequently force the mixtures into fully discrete actions. Moreover, we show how our approach can be extended to partially observable Markov decision processes (POMDPs) for trajectory planning under uncertainty. We validate the approach in a car driving problem where the robot has to switch discrete gears and in a box pushing application where the robot can switch the side of the box to push. The pose and the friction parameters of the pushed box are initially unknown and only indirectly observable.

Connected through hyperedge HE-1 (induced by source paper "hybrid differential dynamic programming for planar manipulation primitives"):
  with members:
    - "tactile dexterity manipulation primitives with tactile feedback"
    - "in hand manipulation via motion cones"
    - "reactive planar manipulation with convex hybrid mpc"
    - "feedback control of the pusher slider system a story of hybrid and underactuated contact dynamics"
    - "a framework for fine robotic assembly"

Connected through hyperedge HE-2 (induced by source paper "a model predictive approach for online mobile manipulation of nonholonomic objects using learned dynamics"):
  with members:
    - "uncertainty averse pushing with model predictive path integral control"
    - "reactive planar manipulation with convex hybrid mpc"
    - "feedback control of the pusher slider system a story of hybrid and underactuated contact dynamics"

Connected through hyperedge HE-3 (induced by source paper "reactive planar manipulation with convex hybrid mpc"):
  with members:
    - "a probabilistic data driven model for planar pushing"
    - "experimental validation of contact dynamics for in hand manipulation"
    - "more than a million ways to be pushed a high fidelity experimental dataset of planar pushing"
    - "feedback control of the pusher slider system a story of hybrid and underactuated contact dynamics"
    - "a convex polynomial force motion model for planar sliding identification and application"

Connected through hyperedge HE-4 (induced by source paper "hybrid ddp in clutter chddp trajectory optimization for hybrid dynamical system in cluttered environments"):
  with members:
    - "feedback control of the pusher slider system a story of hybrid and underactuated contact dynamics"
    - "a hybrid systems model for simple manipulation and self manipulation systems"

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)