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 "toward safe separation distance monitoring from rgb d sensors in human robot interaction"):
  Abstract: The interaction of humans and robots in less constrained environments gains a lot of attention lately and the safety of such interaction is of utmost importance. Two ways of risk assessment are prescribed by recent safety standards: (i) power and force limiting and (ii) speed and separation monitoring. Unlike typical solutions in the industry that are restricted to mere safety zone monitoring, we present a framework that realizes separation distance monitoring between a robot and a human operator in a detailed, yet versatile, transparent, and tunable fashion. The separation distance is assessed pair-wise for all keypoints on the robot and the human body and as such can be selectively modified to account for specific conditions. The operation of this framework is illustrated on a Nao humanoid robot interacting with a human partner perceived by a RealSense RGB-D sensor and employing the OpenPose human skeleton estimation algorithm.

Includes members:
  Member "compact real time avoidance on a humanoid robot for human robot interaction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "safe physical hri toward a unified treatment of speed and separation monitoring together with power and force limiting")
  Member "deepercut a deeper stronger and faster multi person pose estimation model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "higherhrnet scale aware representation learning for bottom up human pose estimation")

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)