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 "observability aware self calibration of visual and inertial sensors for ego motion estimation"):
  Abstract: External effects such as shocks and temperature variations affect the calibration of visual–inertial sensor systems and thus they cannot fully rely on factory calibrations. Re-calibrations performed on short user-collected datasets might yield poor performance since the observability of certain parameters is highly dependent on the motion. In addition, on resource-constrained systems (e.g., mobile phones), full-batch approaches over longer sessions quickly become prohibitively expensive. In this paper, we approach the self-calibration problem by introducing information theoretic metrics to assess the information content of trajectory segments, thus allowing to select the most informative parts from a dataset for calibration purposes. With this approach, we are able to build compact calibration datasets either: 1) by selecting segments from a long session with limited exciting motion or 2) from multiple short sessions where a single session does not necessarily excite all modes sufficiently. Real-world experiments in four different environments show that the proposed method achieves comparable performance to a batch calibration approach, yet, at a constant computational complexity which is independent of the duration of the session.

Includes members:
  Member "maplab an open framework for research in visual inertial mapping and localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "whole body control of a mobile manipulator using end to end reinforcement learning")
  Member "vins mono a robust and versatile monocular visual inertial state estimator":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep drone racing from simulation to reality with domain randomization")
  Member "visual inertial self calibration on informative motion segments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "localization for ground robots on manifold representation integration re parameterization and optimization")
  Member "sampling based motion planning for active multirotor system identification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "build your own visual inertial drone a cost effective and open source autonomous drone")
  Member "observability aware trajectory optimization for self calibration with application to uavs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sensor assignment algorithms to improve observability while tracking targets")

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)