From 44b34d60cfff9705dc146d5aa093a496879eb9d0 Mon Sep 17 00:00:00 2001 From: Shengkang Chen <shengkangchen@Shengkangs-MacBook-Pro.local> Date: Wed, 6 Feb 2019 16:25:59 -0800 Subject: [PATCH] update the readme --- CoLo-AT/README.md | 8 +++++--- README.md | 2 +- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/CoLo-AT/README.md b/CoLo-AT/README.md index d077de3..1bfb80a 100755 --- a/CoLo-AT/README.md +++ b/CoLo-AT/README.md @@ -2,8 +2,10 @@ ## Synopsis -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. -https://drive.google.com/file/d/1NlUM2QXT_KfZkVOJu3Xsm8_QL8OSy6hz/view?usp=sharing +CoLo-AT is the software analysis tool of CoLo using Python. It is a robotic testing environment for cooperative localization using real world dataset[1]. 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 to test the robustness and liabilities of these algorithms, whereas other simulation environments use only simulated data. Users can use CoLo_AT to evaluate their algorithms using the analysis results provided by CoLo-AT + +[CoLo-AT Manual](https://docs.google.com/document/d/1XOe8ZwLlM2DbLjeteLUff9cUuHIKdVW1M-U7jzvrrok/edit#) + ## Features @@ -42,7 +44,7 @@ python Localization_envir.py  -## Available Aglorithm: +## Available Algorithms: 1. LS-Cen 2. LS-CI 3. LS-BDA diff --git a/README.md b/README.md index 1ec9c8b..f6372ca 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ ## Synopsis -CoLo is 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. +Cooperative localization is still a challenging task for cooperative robot control. CoLo is 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. The goal of this project to let users to create and evaluate their own algorithms with some existing algorithms. ## Structure -- GitLab