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CoLo-AT/README.md

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 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#)
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+## [CoLo-AT Manual](https://docs.google.com/document/d/1XOe8ZwLlM2DbLjeteLUff9cUuHIKdVW1M-U7jzvrrok/edit#)
 
 
 ## Features

CoLo-PE/README.md

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 In CoLo-PE, there is a team of ground robots equipped with cameras and a groundtruth data collection system. Each robot can will log its odometry data and measurement data (based on AruCo) into its odometry file and measurement files
 
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+## [CoLo-PE Manual](https://docs.google.com/document/d/1tSIguoFJ5Fdcca0Eqcs4SZFRv2TBLSsm4NYaoaRcUwg/edit?usp=sharing)
 The manual will explain the software and hardware used in CoLo-PE for users to help them create their own experiments in details: 
-[CoLo-PE Manual](https://docs.google.com/document/d/1tSIguoFJ5Fdcca0Eqcs4SZFRv2TBLSsm4NYaoaRcUwg/edit?usp=sharing)
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 ## Running CoLo-PE
 
 1. Make sure the groundtruth data collection system can capture all the needed subjects includes landmarks and robots