ABR_image_transport_tfg wiki!

Author's note:

Welcome to the repository, the end of this proyect was to realice an implementation of an ABR video system for ROS 2 and stablish the theeorical fundamentals needed to bring this concept from multimedia, as i thought it could be a great contribution to robotics. Since this fundamentals are cover now its time to improve it (The fun part), this process and maintaneance will be done on this repository:ABR_Image_Transport

This was my final bachelor's degree work so hope you find it usefull!

Special thanks to my tutor @jmguerreroh for introducing me to ROS 2, guiding me in the success of this project.

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Index

• Introduction

• ABR Logic

• Benchmarks

1. Predictor's Benchmarks

2. Complete algorithm Benchmark

3. Comparison against Theora (Humble)

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In this wiki you will find a completly overview of ABR systems for robotics until today (24/12/24), but you will probably find it updated on ABR_Image_Transport since it is the official continuation.

An Adaptive Bitrate (ABR) system dynamically adjusts the bitrate and resolution of video streams in real-time based on network conditions. By monitoring the transmition, it selects the most suitable bitrate from a predefined "bitrate ladder" to ensure smooth and reliable transmission. This approach guarantees optimal video quality tailored to the current network environment.

This project addresses the challenges of video transmission in ROS 2 by implementing an ABR system for the image_transport package (ROS 2 Humble). The goal is to enhance video streaming performance, ensuring optimal quality and stability in real-time scenarios, even under challenging network conditions (Ex: radiofrequency). This makes it ideal for teleoperated robots.

Since ROS 2 is a network based system and video content consumes a big amount of bandwith, with ABR you can achieve:

• Network adaptation to phisical conditions
• Longer operative distances
• Better resources management
• Others