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 "joint inference of kinematic and force trajectories with visuo tactile sensing"):
  Abstract: To perform complex tasks, robots must be able to interact with and manipulate their surroundings. One of the key challenges in accomplishing this is robust state estimation during physical interactions, where the state involves not only the robot and the object being manipulated, but also the state of the contact itself. In this work, within the context of planar pushing, we extend previous inference-based approaches to state estimation in several ways. We estimate the robot, object, and the contact state on multiple manipulation platforms configured with a vision-based articulated model tracker, and either a biomimetic tactile sensor or a force-torque sensor. We show how to fuse raw measurements from the tracker and tactile sensors to jointly estimate the trajectory of the kinematic states and the forces in the system via probabilistic inference on factor graphs, in both batch and incremental settings. We perform several benchmarks with our framework and show how performance is affected by incorporating various geometric and physics based constraints, occluding vision sensors, or injecting noise in tactile sensors. We also compare with prior work on multiple datasets and demonstrate that our approach can effectively optimize over multi-modal sensor data and reduce uncertainty to find better state estimates.

Includes members:
  Member "robust learning of tactile force estimation through robot interaction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "in hand object pose tracking via contact feedback and gpu accelerated robotic simulation")
  Member "realtime state estimation with tactile and visual sensing for inserting a suction held object":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "making sense of vision and touch learning multimodal representations for contact rich tasks")
  Member "deep forward and inverse perceptual models for tracking and prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "time reversal as self supervision")
  Member "realtime state estimation with tactile and visual sensing application to planar manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust occlusion aware pose estimation for objects grasped by adaptive hands")
  Member "more than a million ways to be pushed a high fidelity experimental dataset of planar pushing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "let s push things forward a survey on robot pushing")
  Member "feedback control of the pusher slider system a story of hybrid and underactuated contact dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fundamental limitations in performance and interpretability of common planar rigid body contact models")

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)