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: "motion planning for a uav with a straight or kinked tether"
  Abstract: This paper develops and compares two motion planning algorithms for a tethered UAV with and without the possibility of the tether contacting the confined and cluttered environment. Tethered aerial vehicles have been studied due to their advantages such as power duration, stability, and safety. However, the disadvantages brought in by the extra tether have not been well investigated by the robotic locomotion community, especially when the tethered agent is locomoting in a non-free space occupied with obstacles. In this work, we propose two motion planning frameworks that (1) reduce the reachable configuration space by taking into account the tether and (2) deliberately plan (and relax) the contact point(s) of the tether with the environment and enable an equivalent reachable configuration space as the non-tethered counterpart would have. Both methods are tested on a physical robot, Fotokite Pro. With our approaches, tethered aerial vehicles could find their applications in confined and cluttered environments with obstacles as opposed to ideal free space, while still maintaining the advantages from the usage of a tether. The motion planning strategies are particularly suitable for marsupial heterogeneous robotic teams, such as visual servoing/assisting for another mobile, tele-operated primary robot.

Connected through hyperedge HE-1 (induced by source paper "tethered aerial visual assistance"):
  with members:
    - "benchmarking tether based uav motion primitives"
    - "robot risk awareness by formal risk reasoning and planning"
    - "autonomous visual assistance for robot operations using a tethered uav"
    - "explicit motion risk representation"
    - "explicit risk aware path planning with reward maximization"
    - "aerial ground collaborative sensing third person view for teleoperation"

Connected through hyperedge HE-2 (induced by source paper "autonomous visual assistance for robot operations using a tethered uav"):
  with members:
    - "benchmarking tether based uav motion primitives"
    - "explicit motion risk representation"
    - "explicit risk aware path planning with reward maximization"

Connected through hyperedge HE-3 (induced by source paper "explicit motion risk representation"):
  with members:
    - "autonomous visual assistance for robot operations using a tethered uav"
    - "explicit risk aware path planning with reward maximization"

Connected through hyperedge HE-4 (induced by source paper "benchmarking tether based uav motion primitives"):
  with members:
    - "autonomous visual assistance for robot operations using a tethered uav"

Connected through hyperedge HE-5 (induced by source paper "robot risk awareness by formal risk reasoning and planning"):
  with members:
    - "autonomous visual assistance for robot operations using a tethered uav"

Connected through hyperedge HE-6 (induced by source paper "robot motion risk reasoning framework"):
  with members:
    - "autonomous visual assistance for robot operations using a tethered uav"

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)