ROS Motion Planning - Coursework

Date: November 2020

Implemented an RRT (Rapidly-exploring Random Tree) motion planning algorithm in Python for the Kuka arm in an ROS simulated environment (RViz) for my Introduction to Robotics (MECE E4602) course.

As part of coursework for this class, I also:
- Computed forward/inverse kinematic control Python scripts that controlled Kuka and UR5 end effectors by subscribing to joint data and publishing desired joint veolicites.
- Performed state estimation by implementing an Extended Kalman filter for a simulated robot using static landmarks to situate itself.
- Implemented a dynamics engine (a.k.a. a physics simulator) for a 2D kinematic chain with an arbitrary number of links via the Newton-Euler algorithm and the simple Euler integration.