CoLo: A Simple and Portable Simulation Environment for Cooperative Localization


CoLo Gitlab

Cooperative localization is still a challenging task for cooperative robot control. CoLo is a robotic simulation environment for cooperative localization or cooperative simultaneous localization and mapping (SLAM) using real world dataset[1] or simulated data. The goal of this project to let users to create and test their own algorithms with some existing algorithms. Compared with other popular robotic simulation environments[2], it has fewer dependencies and more convenient to add localization algorithms without worry much about the robot settings. Moreover, it is able to use both real world data and simulated data to test the robustness and liabilities of these algorithms, whereas other simulation environments use only simulated data.

Features

  1. Real world dataset [1]
  2. Flexible control on the real world dataset
  3. Easy to add and modify algorithms
  4. Preloaded with several existing algorithms
  5. Modularized simulation environment
  6. Basic statistical analytic tools for algorithms

[1]: Leung K Y K, Halpern Y, Barfoot T D, and Liu H H T. “The UTIAS Multi-Robot Cooperative Localization and Mapping Dataset”. International Journal of Robotics Research, 30(8):969–974, July 2011

[2]: Gerkey, Brian P, Richard T Vaughan, and Andrew Howard. “The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems,” 2003, 317–23.


Project Members: Shengkang Chen | Kyle Wong | Cade Mallett