Robot-Trajectory-Optimization

AME Winter Project: Robot Trajectory Optimization using Data & Learning

This repository contains assignments for the AME Winter Project. Please follow the submission instructions carefully.

---

Assignment Structure

• Each assignment has its own folder (e.g. Assignment-01/)
• The assignment problem statement is provided as a PDF inside the assignment folder
• All student submissions must be uploaded as PDF files directly inside the assignment folder
• No additional folders should be created by students

---

Submission Instructions

Step 1: Fork the Repository

• Click the Fork button on the top-right of this repository
• For the upcoming assignments, sync the fork with the base branch each time
• This creates a copy of the repository under your GitHub account

---

Step 2: Make a new branch

• Go to branches, make a new branch named yourname_yoursurname, eg. somya_garg

---

Step 3: Go to the Assignment Folder in the new branch you created

• Open the folder corresponding to the assignment you are submitting
• For Assignment 1, navigate to the folder Assignment-01/

---

Step 4: Upload Your Submission

• Upload all the files contatning your complete submission
• For ex. upload the ipybn or py file for your codebase and a document/pdf explaining the results.

---

Step 5: Commit the Changes

• Commit the uploaded PDF file to your forked repository
• Use a clear commit message (e.g. Add Assignment 1 submission)

---

Step 6: Create a Pull Request

• Go to your forked repository on GitHub
• Click New Pull Request
• Ensure the pull request is made to the yourname_yoursurname branch of the original repository as base and yourname_yoursurame branch of your forked repository as the head branch
• Submit the pull request before the assignment deadline

---

Important Notes

• Do not create folders inside the assignment directory
• Do not modify or delete the assignment PDF
• Do not upload multiple files

---

Deadline

The submission deadline is mentioned in the assignment PDF. Late submissions may not be reviewed.