/state_prediction_tracking

one research for person following based on state tracking

Primary LanguagePython

Repository for a research for person-following in real robot based on state tracking

Overview

soft-state-tracker is a robust target following framework including state tracking and navigation based on CNNs and MLP that can deal with challenging human following tasks with safety and efficiency.

directory structure

  • models ------ state tracker networks and convolutional auto-encoder network
  • tracker ------ state tracker server for evaluate and deploy
  • train ------ train scripts to training all networks
  • AE_train.py -------
  • record.csv ------- record the outputs of two different state-tracker networks in the same test environment for evaluation
  • train.ipynb ------- jupyter notebook file to train the convolutional auto-encoder network
  • utils.py ------- tools for sorting the samples and rename the every item to corrent sequence
  • visualization.py ------ some funtions for visualization

tracker network framework