MoPAT Mk. V: Motion Planning Algorithms Testbed (Research Project)
- Guining Pertin
- Apr 30, 2021
- 1 min read
Updated: Sep 23, 2023
- Dr. Gaurav Trivedi, Dr. Hanumant Singh Shekhawat
//page still in development
To check the documentation on my older site, check
Introduction
If you read research papers on motion planning or swarm robotics, you would often find that these are performed in controlled environments where complete information of the agents/robots can be found easily. While working with Reinforcement Learning simulations, I found the lack of pre-built environments and agents to be quite a drawback for real world testing. Also, the current systems like Vicon Labs were way too expensive and overly powerful for simple 2D simulation and testing. This led me to start my own project on developing a low cost, easy to set-up and highly reconfigurable system on May 2019.
This project went through several iterations over a 3 year period. Mk. I started as an individual project funded through Robotics Club, IITG. Mk. II was an updated version for competitions under Robotics Club. Mk. III included Rahul D and Raneesh Malviya working on the robot implementations while I focused on bringing ROS to the system. Mk. IV was submitted as my 3rd Year Design Project while working with a team of 3 - Me, Sai Manikanta Rishi and Mayank Tantuway. Mk. V included ROS2 as the backend for all the algorithms and ended in April 2021 after my graduation.
Preliminaries
I will cover some basic details on the project first, mainly motion planning and control for differential drive robots.
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