human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "stance locomotion adaptation over soft terrain"):
  Abstract: Whole-body Control (WBC) has emerged as an important framework in locomotion control for legged robots. However, most of WBC frameworks fail to generalize beyond rigid terrains. Legged locomotion over soft terrain is difficult due to the presence of unmodeled contact dynamics that WBCs do not account for. This introduces uncertainty in locomotion and affects the stability and performance of the system. In this paper, we propose a novel soft terrain adaptation algorithm called STANCE: Soft Terrain Adaptation and Compliance Estimation. STANCE consists of a WBC that exploits the knowledge of the terrain to generate an optimal solution that is contact consistent and an online terrain compliance estimator that provides the WBC with terrain knowledge. We validated STANCE both in simulation and experiment on the Hydraulically actuated Quadruped (HyQ) robot, and we compared it against the state of the art WBC. We demonstrated the capabilities of STANCE with multiple terrains of different compliances, aggressive maneuvers, different forward velocities, and external disturbances. STANCE allowed HyQ to adapt online to terrains with different compliances (rigid and soft) without pre-tuning. HyQ was able to successfully deal with the transition between different terrains and showed the ability to differentiate between compliances under each foot.

Includes members:
  Member "heuristic planning for rough terrain locomotion in presence of external disturbances and variable perception quality":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "feasible region an actuation aware extension of the support region")
  Member "frequency aware model predictive control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "whole body mpc for a dynamically stable mobile manipulator")
  Member "dynamic locomotion for passive ankle biped robots and humanoids using whole body locomotion control":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data efficient and safe learning for locomotion via simplified model")
  Member "passive whole body control for quadruped robots experimental validation over challenging terrain":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning how to walk warm starting optimal control solver with memory of motion")
  Member "contact implicit optimization of locomotion trajectories for a quadrupedal microrobot":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "scaling down an insect size microrobot hamr vi into hamr jr")
  Member "whole body nonlinear model predictive control through contacts for quadrupeds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "guided constrained policy optimization for dynamic quadrupedal robot locomotion")
  Member "robust whole body motion control of legged robots":
    also connected through other hyperedges:
      (none)
  Member "robot impedance control and passivity analysis with inner torque and velocity feedback loops":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "feedback mpc for torque controlled legged robots")

Question: Please tell me which class the source paper 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)