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 efficient reachability based framework for provably safe autonomous navigation in unknown environments"):
  Abstract: Real-world autonomous vehicles often operate in a priori unknown environments. Since most of these systems are safety-critical, it is important to ensure they operate safely in the face of environment uncertainty, such as unseen obstacles. Current safety analysis tools enable autonomous systems to reason about safety given full information about the state of the environment a priori. However, these tools do not scale well to scenarios where the environment is being sensed in real time, such as during navigation tasks. In this work, we propose a novel, real-time safety analysis method based on Hamilton-Jacobi reachability that provides strong safety guarantees despite environment uncertainty. Our safety method is planner-agnostic and provides guarantees for a variety of mapping sensors. We demonstrate our approach in simulation and in hardware to provide safety guarantees around a state-of-the-art vision-based, learning-based planner.

Includes members:
  Member "combining optimal control and learning for visual navigation in novel environments":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "citylearn diverse real world environments for sample efficient navigation policy learning")
  Member "safe and complete real time planning and exploration in unknown environments":
    also connected through other hyperedges:
      (none)
  Member "a lyapunov based approach to safe reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "constrained upper confidence reinforcement learning")
  Member "safe motion planning in unknown environments optimality benchmarks and tractable policies":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "autonomous navigation in unknown environments using sparse kernel based occupancy mapping")
  Member "a general safety framework for learning based control in uncertain robotic systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to walk in the real world with minimal human effort")
  Member "fastrack a modular framework for fast and guaranteed safe motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "safety considerations in deep control policies with safety barrier certificates under uncertainty")
  Member "constrained policy optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust deep reinforcement learning against adversarial perturbations on observations")
  Member "provably safe and robust drone routing via sequential path planning a case study in san francisco and the bay area":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "modeling cyber physical human systems via an interplay between reinforcement learning and game theory")

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)