human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Predictive autonomous robot navigation"
  Abstract: This paper considers the problem of a robot navigating in a crowded or congested environment. A robot operating in such an environment can get easily blocked by moving humans and other objects. To deal with this problem it is proposed to attempt to predict the motion trajectory of humans and obstacles. Two kinds of prediction are considered: short-term and long-term. The short-term prediction refers to the one-step ahead prediction and the long-term to the prediction of the final destination point of the obstacle's movement. The robot movement is controlled by a partially observable Markov decision process (POMDP). POMDPs are utilized because of their ability to model information about the robot's location and sensory information in a probabilistic manner. The solution of a POMDP is computationally expensive and thus a hierarchical representation of POMDPs is used.

Connected through hyperedge HE-1 (induced by source paper "Mobile robot localization by tracking geometric beacons"):
  with members:
    - "Sensor models and multisensor integration"
    - "Vehicle Localization Using In-Vehicle Pitch Data and Dynamical Models"
    - "Global A-Optimal Robot Exploration in SLAM"
    - "Robot Localization Using Omnidirectional Color Images"

Connected through hyperedge HE-2 (induced by source paper "Learning Motion Patterns of People for Compliant Robot Motion"):
  with members:
    - "A model of distributional handing interaction for a mobile robot"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science