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 "dynamic markers uav landing proof of concept"):
  Abstract: In this paper, we introduce a dynamic fiducial marker which can change its appearance according to the spatio-temporal requirements of the visual perception task of a mobile robot using a camera as sensor. We present a control scheme to dynamically change the appearance of the marker such that the pose of the robot can be optimally estimated from the camera image. The appearance control takes into account the dependency of the estimation quality on the current pose of the camera in relation to the marker.Hence, we realize a tight coupling between the visual pose control of the mobile robot and the appearance control of the dynamic fiducial marker. Further on, we discuss the implications of time delays because of processing time and communication delays between the robot and the marker. Finally, we propose a real time dynamic marker visual servoing control scheme for quadcopter landing and evaluate the performance on a real world example.

Includes members:
  Member "moma visual mobile marker odometry":
    also connected through other hyperedges:
      (none)
  Member "mapping and localization from planar markers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ucoslam simultaneous localization and mapping by fusion of keypoints and squared planar markers")
  Member "an open source fiducial based visual inertial motion capture system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "confusion sensor fusion for complex robotic systems using nonlinear optimization")
  Member "mutual localization two camera relative 6 dof pose estimation from reciprocal fiducial observation":
    also connected through other hyperedges:
      (none)

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)