CoLo: A Performance Evaluation System for Multi-robot Cooperative Localization Algorithms

Open source toolchain to characterize two-dimensional cooperative localization algorithms


Project Lead: Shengkang Chen Project Members: Ben Limpanukorn


CoLo Gitlab

This paper describes CoLo - a performance evaluation system for two-dimensional cooperative localization algorithms. The system consists of a physical experiment (CoLo-PE) for data collection and a software analysis tool (CoLo-AT) using real-world datasets to evaluate the performances of users' cooperative localization algorithms. CoLo allows researchers to conveniently add their cooperative localization algorithms and test them extensively on different real-world datasets with various settings.

(Accepted) S. Chen, and A. Mehta, "CoLo: A Performance Evaluation System for Multi-robot Cooperative Localization Algorithmsā€¯ in 2019 International Conference on Robotics and Automation (ICRA), May. 2019.

Features

  1. Easy to setup and run
  2. Test with real world dataset
  3. Flexible control on the real world dataset
  4. Easy to add and modify algorithms
  5. Preloaded with several existing algorithms
  6. Modularized simulation environment for CoLo-AT

Past Project Members: Clara Chun | Kyle Wong | Cade Mallett


CoLo Structure