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: "hierarchical planning of dynamic movements without scheduled contact sequences"
  Abstract: Most animal and human locomotion behaviors for solving complex tasks involve dynamic motions and rich contact interaction. In fact, complex maneuvers need to consider dynamic movement and contact events at the same time. We present a hierarchical trajectory optimization approach for planning dynamic movements with unscheduled contact sequences. We compute whole-body motions that achieve goals that cannot be reached in a kinematic fashion. First, we find a feasible CoM motion according to the centroidal dynamics of the robot. Then, we refine the solution by applying the robot's full-dynamics model, where the feasible CoM trajectory is used as a warm-start point. To accomplish the unscheduled contact behavior, we use complementarity constraints to describe the contact model, i.e. environment geometry and non-sliding active contacts. Both optimization phases are posed as Mathematical Program with Complementarity Constraints (MPCC). Experimental trials demonstrate the performance of our planning approach in a set of challenging tasks.

Connected through hyperedge HE-1 (induced by source paper "contact planning for the anymal quadruped robot using an acyclic reachability based planner"):
  with members:
    - "learning agile and dynamic motor skills for legged robots"
    - "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization"
    - "a convex model of momentum dynamics for multi contact motion generation"
    - "planning and execution of dynamic whole body locomotion for a hydraulic quadruped on challenging terrain"

Connected through hyperedge HE-2 (induced by source paper "learning a structured neural network policy for a hopping task"):
  with members:
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "emergence of locomotion behaviours in rich environments"
    - "proximal policy optimization algorithms"
    - "structured contact force optimization for kino dynamic motion generation"
    - "trust region policy optimization"
    - "learning contact rich manipulation skills with guided policy search"
    - "fast and accurate deep network learning by exponential linear units elus"
    - "end to end training of deep visuomotor policies"

Connected through hyperedge HE-3 (induced by source paper "whole body nonlinear model predictive control through contacts for quadrupeds"):
  with members:
    - "the control toolbox an open source c library for robotics optimal and model predictive control"
    - "a family of iterative gauss newton shooting methods for nonlinear optimal control"
    - "an efficient optimal planning and control framework for quadrupedal locomotion"
    - "automatic differentiation of rigid body dynamics for optimal control and estimation"
    - "trajectory optimization through contacts and automatic gait discovery for quadrupeds"
    - "projection based whole body motion planning for legged robots"
    - "planning and execution of dynamic whole body locomotion for a hydraulic quadruped on challenging terrain"
    - "trajectory generation for multi contact momentum control"

Connected through hyperedge HE-4 (induced by source paper "contact implicit trajectory optimization based on a variable smooth contact model and successive convexification"):
  with members:
    - "a comparative analysis of contact models in trajectory optimization for manipulation"
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "a family of iterative gauss newton shooting methods for nonlinear optimal control"
    - "automatic differentiation of rigid body dynamics for optimal control and estimation"
    - "trajectory optimization through contacts and automatic gait discovery for quadrupeds"

Connected through hyperedge HE-5 (induced by source paper "a comparative analysis of contact models in trajectory optimization for manipulation"):
  with members:
    - "whole body nonlinear model predictive control through contacts for quadrupeds"
    - "trajectory optimization through contacts and automatic gait discovery for quadrupeds"

Connected through hyperedge HE-6 (induced by source paper "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization"):
  with members:
    - "motion planning for quadrupedal locomotion coupled planning terrain mapping and whole body control"
    - "the actuation consistent wrench polytope awp and the feasible wrench polytope fwp"
    - "fast trajectory optimization for legged robots using vertex based zmp constraints"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "trajectory optimization through contacts and automatic gait discovery for quadrupeds"):
  with members:
    - "momentum control with hierarchical inverse dynamics on a torque controlled humanoid"

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)