CS5757: Optimization Methods for Robotics

Spring 2026 Repo for CS5757 - Optimization Methods for Robotics.

Homework Assignments

The assignments/ folder contains homework assignments: Each homework assignment is in its own directory:

• hw0/ - Homework 0
• hw1/ - Homework 1
• etc.

Getting Started

1. Clone this repository
2. Navigate to the relevant homework directory
3. Follow the instructions in the homework-specific README

Requirements

See individual homework directories for specific dependencies.

Submission

Please submit on Gradescope, more details can be found on the website

Questions

For questions about assignments, please use the course Ed discussion forum or attend office hours.

Lecture Materials

The lectures/ folder contains lecture materials: Each lectures have its own directory: This directory contains example code and demos used in lecture for CS 5757: Optimization Methods for Robotics, as well as lecture notes.

Environment Setup

Choose one of the following methods to set up your Python environment.

Option 1: Using uv (Recommended)

uv is a fast Python package manager. Install it first if you haven't already.

# Create and activate virtual environment
uv venv --python 3.12
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
uv pip install -r requirements.txt

To register the environment as a Jupyter kernel:

uv pip install ipykernel
python -m ipykernel install --user --name=cs5757 --display-name="CS 5757"

Option 2: Using conda

# Create a new conda environment
conda create -n cs5757 python=3.12 -y
conda activate cs5757

# Install dependencies
pip install -r requirements.txt

To register the environment as a Jupyter kernel:

conda install ipykernel -y
python -m ipykernel install --user --name=cs5757 --display-name="CS 5757"

Running the Notebooks

Jupyter Lab / Notebook

# If not already installed
pip install jupyterlab  # or: conda install jupyterlab

# Launch
jupyter lab

Select the CS 5757 kernel from the kernel dropdown.

VS Code

1. Install the Jupyter extension for VS Code.
2. Open any .ipynb file.
3. Click "Select Kernel" in the top-right corner of the notebook.
4. Choose "CS 5757" from the list (or select the Python interpreter from your virtual environment).

Note: If the kernel doesn't appear, reload VS Code or run the ipykernel install command above. If you're using uv, the kernel may appear as .venv.

Updating Dependencies

Requirements may be updated over the semester. If you encounter missing packages, re-run the install command:

#cd
cd lectures/

# uv
uv pip install -r requirements.txt

# conda
pip install -r requirements.txt