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: "3lp a linear 3d walking model including torso and swing dynamics"
  Abstract: In this paper, we present a new model of biped locomotion which is composed of three linear pendulums (one per leg and one for the whole upper body) to describe stance, swing and torso dynamics. In addition to double support, this model has different actuation possibilities in the swing hip and stance ankle which could be widely used to produce different walking gaits. Without the need for numerical time-integration, closed-form solutions help finding periodic gaits which could be simply scaled in certain dimensions to modulate the motion online. Thanks to linearity properties, the proposed model can provide a computationally fast platform for model predictive controllers to predict the future and consider meaningful inequality constraints to ensure feasibility of the motion. Such property is coming from describing dynamics with joint torques directly and therefore, reflecting hardware limitations more precisely, even in the very abstract high level template space. The proposed model produces human-like torque and ground reaction force profiles and thus, compared to point-mass models, it is more promising for precise control of humanoid robots. Despite being linear and lacking many other features of human walking like CoM excursion, knee flexion and ground clearance, we show that the proposed model can predict one of the main optimality trends in human walking, i.e. nonlinear speed-frequency relationship. In this paper, we mainly focus on describing the model and its capabilities, comparing it with human data and calculating optimal human gait variables. Setting up control problems and advanced biomechanical analysis still remain for future works.

Connected through hyperedge HE-1 (induced by source paper "a robust model based biped locomotion framework based on three mass model from planning to control"):
  with members:
    - "footstep planning for autonomous walking over rough terrain"
    - "a fast and stable omnidirectional walking engine for the nao humanoid robot"
    - "a whole body model predictive control scheme including external contact forces and com height variations"

Connected through hyperedge HE-2 (induced by source paper "optimal reduced order modeling of bipedal locomotion"):
  with members:
    - "rapid trajectory optimization using c frost with illustration on a cassie series dynamic walking biped"
    - "rapid bipedal gait design using c frost with illustration on a cassie series robot"
    - "comparative design scaling and control of appendages for inertial reorientation"

Connected through hyperedge HE-3 (induced by source paper "scalable closed form trajectories for periodic and non periodic human like walking"):
  with members:
    - "push recovery with stepping strategy based on time projection control"
    - "straight leg walking through underconstrained whole body control"
    - "emergence of locomotion behaviours in rich environments"

Connected through hyperedge HE-4 (induced by source paper "a new time projecting controller based on 3lp model to recover intermittent pushes"):
  with members:
    - "an efficiently solvable quadratic program for stabilizing dynamic locomotion"
    - "real time planning with primitives for dynamic walking over uneven 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)