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 "continuous time gaussian process motion planning via probabilistic inference"):
  Abstract: We introduce a novel formulation of motion planning, for continuous-time trajectories, as probabilistic inference. We first show how smooth continuous-time trajectories can be represented by a smal...

Includes members:
  Member "steap simultaneous trajectory estimation and planning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spatial concept based navigation with human speech instructions via probabilistic inference on bayesian generative model")
  Member "approximately optimal continuous time motion planning and control via probabilistic inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "riemannian motion policy fusion through learnable lyapunov function reshaping")
  Member "functional gradient motion planning in reproducing kernel hilbert spaces":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "functional path optimisation for exploration in continuous occupancy maps")
  Member "batch informed trees bit sampling based optimal planning via the heuristically guided search of implicit random geometric graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "drrt scalable and informed asymptotically optimal multi robot motion planning")
  Member "batch nonlinear continuous time trajectory estimation as exactly sparse gaussian process regression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "steap simultaneous trajectory estimation and planning")
  Member "incremental sampling based algorithms for optimal motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bayesian local sampling based planning")

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)