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Benchmarking of Natural Language Understanding models in context of service robots

This repository contains the code, datasets, and suplemental materials for "Tell Your Robot What To Do: Evaluation of Natural Language Models for Robot Command Processing" by Erick Romero Kramer, Argentina Ortega Sainz, Alex Mitrevski, and Paul G. Ploeger.

Models used for Benchmarking

Repository structure

  • code/
    • ecg_framework_code
      • Required repository for ECG
    • ecg_grammars
      • Contains grammars generated for our Benchmarking
    • ecg_robot_code
      • Modified version of ECG to extract the semantic specifications
    • ecg_workbench_release
      • Tool used to generated ECG grammar files
    • lu4r
      • Empty folder
    • rasa_models
      • Contains the nlu models and scripts to generate the training datasets
    • mbot
      • Contains the trained classifiers and scripts to generate the training datasets
  • datasets/
    • GPSR category 1 (Single and multiple actions)
    • GPSR category 2 (Single and multiple actions)
    • ROPOD
  • docs
    • RnD Report
      • Detailed information about the related work presented in the paper.
      • Detailed guideline about the models selected (how the work, how to train/adapt them, and how to use them).
      • Explicit description of the process followed during the benchmarking.
    • paper.pdf - PENDING

Notes:

  • Pending to add link to the published version of the paper.
  • Due to space limitations, the code can be downloaded from here

Demo:

  • Navigation Commands using Mbot - Video

Author

Erick Romero Kramer - email - University email