Portfolio-of-Robotics-Algorithms

My personal portfolio of robot learning algorithms, from course materials in 517 and 650 at UPenn.

• This repository is continuously updated with new algorithms and implementations as I learn them.

• Last updated: 2024-Apr-6

Table of Contents

1. Optimal Control and Trajectory Optimization: LQR, MPC, Energy Shaping, iLQR, Collocation, Min-snap

2. State Estimation: Kalman Filter, EKF, UKF, Particle Filter

3. Perception: 2D SLAM with PF, NeRF (to be updated)

4. Planning: Dynamic Programming, etc (to be updated)

5. Robot Learning: HMM, DQN (to be updated)

Results and Demos

1. Energy shaping of a cartpole system

2. LQR for a 2D quadrotor

3. MPC for a 2D quadrotor

4. iLQR

5. Direct Collocation

6. Min-snap

7. Kalman Filter, EKF, & UKF for quaternions

• Using EKF to estimate a system parameter

  

8. 2D SLAM with Particle Filter

9. NeRF

10. Dynamic Programming

• Value Iteration

  

• Policy Iteration

  

Acknowledgements

650 course materials are from Prof. Pratik Chaudhari, 517 course materials are from Prof. Michael Posa.

During my implementation, I also learned a lot from Anirudh Kailaje (https://github.com/KailajeAnirudh). Please also star his wonderful repositories if you find mine helpful.