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: "a decentralized multi agent unmanned aerial system to search pick up and relocate objects"
  Abstract: We present a fully integrated autonomous multi­robot aerial system for finding and collecting moving and static objects with unknown locations. This task addresses multiple relevant problems in search and rescue (SAR) robotics such as multi-agent aerial exploration, object detection and tracking, and aerial gripping. Usually, the community tackles these problems individually but the integration into a working system generates extra complexity which is rarely addressed. We show that this task can be solved reliably using only simple components. Our decentralized system uses accurate global state estimation, reactive collision avoidance, and sweep plan­ning for multi-agent exploration. Objects are detected, tracked, and picked up using blob detection, inverse 3D-projection, Kalman filtering, visual-servoing, and a magnetic gripper. We evaluate the individual components of our system on the real platform. The full system has been deployed successfully in various public demonstrations, field tests, and the Mohamed Bin Zayed International Robotics Challenge 2017 (MBZIRC). Among the contestants we showed reliable performances and reached second place out of 17 in the individual challenge.

Connected through hyperedge HE-1 (induced by source paper "in flight range optimization of multicopters using multivariable extremum seeking with adaptive step size"):
  with members:
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-2 (induced by source paper "aerial ground collaborative sensing third person view for teleoperation"):
  with members:
    - "3d registration of aerial and ground robots for disaster response an evaluation of features descriptors and transformation estimation"
    - "aerial picking and delivery of magnetic objects with mavs"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"

Connected through hyperedge HE-3 (induced by source paper "team nimbro at mbzirc 2017 fast landing on a moving target and treasure hunting with a team of mavs"):
  with members:
    - "fast autonomous flight in warehouses for inventory applications"
    - "nimbro rescue solving disaster response tasks through mobile manipulation robot momaro"
    - "the eth mav team in the mbz international robotics challenge"

Connected through hyperedge HE-4 (induced by source paper "vision based distributed formation control of unmanned aerial vehicles"):
  with members:
    - "monocular vision based collaborative localization for micro aerial vehicle swarms"
    - "robust distributed planar formation control for higher order holonomic and nonholonomic agents"
    - "quest a quaternion based approach for camera motion estimation from minimal feature points"

Connected through hyperedge HE-5 (induced by source paper "robust 3d distributed formation control with application to quadrotors"):
  with members:
    - "robust distributed planar formation control for higher order holonomic and nonholonomic agents"

Connected through hyperedge HE-6 (induced by source paper "the eth mav team in the mbz international robotics challenge"):
  with members:
    - "robust collaborative object transportation using multiple mavs"
    - "nonlinear model predictive control for multi micro aerial vehicle robust collision avoidance"
    - "aerial picking and delivery of magnetic objects with mavs"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"

Connected through hyperedge HE-7 (induced by source paper "robust collaborative object transportation using multiple mavs"):
  with members:
    - "aerial picking and delivery of magnetic objects with mavs"
    - "unscented external force and torque estimation for quadrotors"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"

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)