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: "crocoddyl an efficient and versatile framework for multi contact optimal control"
  Abstract: We introduce Crocoddyl (Contact RObot COntrol by Differential DYnamic Library), an open-source framework tailored for efficient multi-contact optimal control. Crocoddyl efficiently computes the state trajectory and the control policy for a given predefined sequence of contacts. Its efficiency is due to the use of sparse analytical derivatives, exploitation of the problem structure, and data sharing. It employs differential geometry to properly describe the state of any geometrical system, e.g. floating-base systems. We have unified dynamics, costs, and constraints into a single concept -- action -- for greater efficiency and easy prototyping. Additionally, we propose a novel multiple-shooting method called Feasibility-prone Differential Dynamic Programming (FDDP). Our novel method shows a greater globalization strategy compared to classical Differential Dynamic Programming (DDP) algorithms, and it has similar numerical behavior to state-of-the-art multiple-shooting methods. However, our method does not increase the computational complexity typically encountered by adding extra variables to describe the gaps in the dynamics. Concretely, we propose two modifications to the classical DDP algorithm. First, the backward pass accepts infeasible state-control trajectories. Second, the rollout keeps the gaps open during the early "exploratory" iterations (as expected in multiple-shooting methods). We showcase the performance of our framework using different tasks. With our method, we can compute highly-dynamic maneuvers for legged robots (e.g. jumping, front-flip) in the order of milliseconds.

Connected through hyperedge HE-1 (induced by source paper "optimizing dynamic trajectories for robustness to disturbances using polytopic projections"):
  with members:
    - "optimisation of body ground contact for augmenting whole body loco manipulation of quadruped robots"
    - "a differentiable augmented lagrangian method for bilevel nonlinear optimization"
    - "comparing metrics for robustness against external perturbations in dynamic trajectory optimization"
    - "application of wrench based feasibility analysis to the online trajectory optimization of legged robots"
    - "a family of iterative gauss newton shooting methods for nonlinear optimal control"
    - "julia a fresh approach to numerical computing"
    - "on computing the shadows and slices of polytopes"

Connected through hyperedge HE-2 (induced by source paper "learning how to walk warm starting optimal control solver with memory of motion"):
  with members:
    - "memory of motion for warm starting trajectory optimization"
    - "passive whole body control for quadruped robots experimental validation over challenging terrain"
    - "differential dynamic programming for multi phase rigid contact dynamics"
    - "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization"
    - "trajectory optimization through contacts and automatic gait discovery for quadrupeds"
    - "planning and execution of dynamic whole body locomotion for a hydraulic quadruped on challenging terrain"

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)