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 "an informative path planning framework for uav based terrain monitoring"):
  Abstract: Unmanned aerial vehicles (UAVs) represent a new frontier in a wide range of monitoring and research applications. To fully leverage their potential, a key challenge is planning missions for efficient data acquisition in complex environments. To address this issue, this article introduces a general informative path planning (IPP) framework for monitoring scenarios using an aerial robot. The approach is capable of mapping either discrete or continuous target variables on a terrain using variable-resolution data received from probabilistic sensors. During a mission, the terrain maps built online are used to plan information-rich trajectories in continuous 3-D space by optimizing initial solutions obtained by a course grid search. Extensive simulations show that our approach is more efficient than existing methods. We also demonstrate its real-time application on a photorealistic mapping scenario using a publicly available dataset.

Includes members:
  Member "sampling based incremental information gathering with applications to robotic exploration and environmental monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "active learning for uav based semantic mapping")
  Member "hindsight is only 50 50 unsuitability of mdp based approximate pomdp solvers for multi resolution information gathering":
    also connected through other hyperedges:
      (none)
  Member "a data driven approach for autonomous motion planning and control in off road driving scenarios":
    also connected through other hyperedges:
      (none)
  Member "algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "elkppnet an edge aware neural network with large kernel pyramid pooling for learning discriminative features in semantic segmentation")
  Member "multiresolution mapping and informative path planning for uav based terrain monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "building an aerial ground robotics system for precision farming")
  Member "dynamic system identification and control for a cost effective open source vtol mav":
    also connected through other hyperedges:
      (none)
  Member "weednet dense semantic weed classification using multispectral images and mav for smart farming":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "modeling curiosity in a mobile robot for long term autonomous exploration and monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "active reward learning for co robotic vision based exploration in bandwidth limited environments")

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)