From 5cb127a3739878e388e1a867408ed3c8f540bb5d Mon Sep 17 00:00:00 2001 From: "Shengkang (William) Chen" <billyskc@ucla.edu> Date: Fri, 15 Sep 2023 18:30:54 +0000 Subject: [PATCH] Update README.md --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index b7895a6..d44bbbb 100644 --- a/README.md +++ b/README.md @@ -2,14 +2,14 @@ ## Synopsis -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. +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 is to let users create and evaluate their own algorithms with some existing algorithms. [Project Website](https://uclalemur.com/research/colo-simulation-environment-for-cooperative-localization) ## Structure There are two main parts in CoLo: a physical experiment (CoLo-PE) for data collection and a software analysis tool (CoLo-AT) -In CoLo-PE, it will shows the requriment hardwares and softwares needed for setting up the the physical experiments. -In CoLo-AT, users can load their localization algorithms and test their performances using different datasets on various settings. -Each parts can be used independetly for users' needs. +In CoLo-PE, it will show the required hardware and software needed for setting up the physical experiments. +In CoLo-AT, users can load their localization algorithms and test their performances using different datasets in various settings. +Each part can be used independently for users' needs. ## Cite this work ``` -- GitLab