human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "an effective algorithmic framework for near optimal multi robot path planning"
  Abstract: We present a centralized algorithmic framework for solving multi-robot path planning problems in general, two-dimensional, continuous environments while minimizing globally the task completion time. The framework obtains high levels of effectiveness through the composition of an optimal discretization of the continuous environment and the subsequent fast, near-optimal resolution of the resulting discrete planning problem. This principled approach achieves orders of magnitudes better performance with respect to both speed and the supported robot density. For a wide variety of environments, our method is shown to compute globally near-optimal solutions for fifty robots in seconds with robots packed close to each other. In the extreme, the method can consistently solve problems with hundreds of robots that occupy over 30% of the free space.

Connected through hyperedge HE-1 (induced by source paper "deepmnavigate deep reinforced multi robot navigation unifying local global collision avoidance"):
  with members:
    - "densecavoid real time navigation in dense crowds using anticipatory behaviors"
    - "learning to communicate a machine learning framework for heterogeneous multi agent robotic systems"
    - "motion planning among dynamic decision making agents with deep reinforcement learning"
    - "fully distributed multi robot collision avoidance via deep reinforcement learning for safe and efficient navigation in complex scenarios"
    - "towards optimally decentralized multi robot collision avoidance via deep reinforcement learning"
    - "from perception to decision a data driven approach to end to end motion planning for autonomous ground robots"
    - "socially aware motion planning with deep reinforcement learning"
    - "uncertainty aware reinforcement learning for collision avoidance"

Connected through hyperedge HE-2 (induced by source paper "towards scalable continuous time trajectory optimization for multi robot navigation"):
  with members:
    - "trajectory generation for multiagent point to point transitions via distributed model predictive control"
    - "online trajectory generation with distributed model predictive control for multi robot motion planning"
    - "safe aggressive quadrotor flight via reachability based trajectory design"
    - "continuous time trajectory optimization for decentralized multi robot navigation"
    - "safe certificate based maneuvers for teams of quadrotors using differential flatness"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"

Connected through hyperedge HE-3 (induced by source paper "a modular framework for motion planning using safe by design motion primitives"):
  with members:
    - "a framework for multi vehicle navigation using feedback based motion primitives"
    - "scalable asymptotically optimal multi robot motion planning"
    - "downwash aware trajectory planning for large quadrotor teams"
    - "funnel libraries for real time robust feedback motion planning"

Connected through hyperedge HE-4 (induced by source paper "sear a polynomial time multi robot path planning algorithm with expected constant factor optimality guarantee"):
  with members:
    - "a portable 3d printing enabled multi vehicle platform for robotics research and education"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "a linear time algorithm for the feasibility of pebble motion on graphs"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"
    - "k color multi robot motion planning"

Connected through hyperedge HE-5 (induced by source paper "a portable 3d printing enabled multi vehicle platform for robotics research and education"):
  with members:
    - "safe remote access swarm robotics research on the robotarium"

Question: Please tell me which class the center node 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)