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 "a lexicographic search method for multi objective motion planning"):
  Abstract: We consider multi-objective motion planning problems in which two competing resources are penalized hierarchically. The highest-priority resource takes on non-negative values over robot paths, and is frequently zero-valued. This is intended to capture problems in which robots must manage a resource such as collision risk, exposure to threats, or access to valuable measurements, whose consideration is critical in some regions of the environment, and unimportant in others. This leaves freedom for tie-breaking with respect to a secondary resource, which we assume to be a strictly positive quantity consumed by the robot, such as distance traveled, energy expended or time elapsed. We leverage the paradigm of lexicographic optimization and apply it for the first time to graph search over roadmaps. Specifically, our "lexicographic search" is employed in concert with probabilistic roadmaps to solve motion planning problems under various non-negative cost functions motivated by real-world applications.

Includes members:
  Member "a bi criteria path planning algorithm for robotics applications":
    also connected through other hyperedges:
      (none)
  Member "incremental sampling based algorithm for minimum violation motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "revisiting the asymptotic optimality of rrt")
  Member "sampling based algorithms for optimal motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")

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)