PhD dissertation: Bootstrapping Vehicles 2012-11-07

Art by striatic.

Andrea Censi. Bootstrapping Vehicles: a formal approach to unsupervised sensorimotor learning based on invariance. Technical Report, California Institute of Technology, 2012. pdf supp. material slidesbibtex

This is version 1.3 of my dissertation; I was not satisfied with the "official" 1.0 version, and I'm still adding material that I didn't have time to write. Because this is still a work in progress, any feedback is most appreciated.



Data used for calibration by correlation.

other videos
for Chapter 11

Vehicles navigation using bootstrapped models.

other videos
for Chapters 12-13

Larning BGDS model with streaming data

other videos
for Chapter 14+


All software is available for download from various GitHub projects (I am working on a one-click installation for Amazon EC2; inquire if interested).

These are the main pieces:

  • boot12env is the "root" repository that contains scripts for setting up a virtual environment and checking out the other packages.
  • BootOlympics is the package responsible for interfacing agents and robots, loading/saving data and running the benchmarks, such as prediction, servoing, etc.
    • bvapps contains the configuration files for the simulations/experiments.
    • boot_agents contains the implementation of the agents (BDS, BGDS, DDS, etc.).
  • PyVehicles is used to run the Vehicles simulations.
  • PyGeometry implements all differential geometry functions.

These are miscellaneous utilities for creating reports, videos, and general plumbing: