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 "build your own visual inertial drone a cost effective and open source autonomous drone"):
  Abstract: This article describes an approach to building a cost-effective and research-grade visual-inertial (VI) odometry-aided vertical takeoff and landing (VTOL) platform. We utilize an off-the-shelf VI sensor, an onboard computer, and a quadrotor platform, all of which are factory calibrated and mass produced, thereby sharing similar hardware and sensor specifications [e.g., mass, dimensions, intrinsic and extrinsic of camera-inertial measurement unit (IMU) systems, and signal-to-noise ratio]. We then perform system calibration and identification, enabling the use of our VI odometry, multisensor fusion (MSF), and model predictive control (MPC) frameworks with off-the-shelf products. This approach partially circumvents the tedious parameter-tuning procedures required to build a full system. The complete system is extensively evaluated both indoors using a motioncapture system and outdoors using a laser tracker while performing hover and step responses and trajectory-following tasks in the presence of external wind disturbances. We achieve root-mean-square (rms) pose errors of 0.036 m with respect to reference hover trajectories. We also conduct relatively long distance (.180 m) experiments on a farm site, demonstrating a 0.82% drift error of the total flight distance. This article conveys the insights we acquired about the platform and sensor module and offers open-source code with tutorial documentation to the community.

Includes members:
  Member "sampling based motion planning for active multirotor system identification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "observability aware self calibration of visual and inertial sensors for ego motion estimation")
  Member "control of a quadrotor with reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to fly via deep model based reinforcement learning")
  Member "visual inertial monocular slam with map reuse":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")
  Member "autonomous landing of a multirotor micro air vehicle on a high velocity ground vehicle":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "long duration fully autonomous operation of rotorcraft unmanned aerial systems for remote sensing data acquisition")
  Member "on manifold preintegration theory for fast and accurate visual inertial navigation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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)