Collection of Python implementations of Robotics and Computer Vision theories taught in

1. University of Pennsylvania Robotics Specialization
2. University of Cambridge Computer Vision
3. University of Cambridge Robotics
4. University of Cambridge Reinforcement Learning and Decision Making
5. Robot Ignite Academy [link]

Aims of this repo are to rewrite all MATLAB demos from the online courses into Python to develop a deeper understanding about those Robotics and Computer Vision concepts, and provide more readable scripts for beginners to begin their learning about Robotics. [**Mobility course is coming soon!]

• Python 3.7.4 + numpy 1.16.5 + scipy 1.3.1 + matplotlib 3.1.1 + yaml 5.1.2 + open-cv 3.4.2 + glob 0.7 + tqdm 4.36.1 + sympy 1.4 + slycot 0.3.5.0 + pydobot

• Quadcopter 1D + Quadcopter 2D
• Dijkstra Algorithm + A-star Algorithm + Configuration Space + Potential Field Path
• 2D Homography + 3D Homography + Optical Track + Point Cloud + Calibration
• Kalman Filter + Occupancy Grid Map + Particle Localization
• Proportional-Derivative Control + Proportional-Derivative Track Arm + Solve Ordinary Differential Equation + Estimated Kalman Filter
• Mobile Inverted Pendulum + Linear–quadratic regulator Mobile Inverted Pendulum + Proportional–Integral–Derivative controller Mobile Inverted Pendulum
• Value Iteration + Policy Iteration + State–Action–Reward–State–Action + Q-Learning
• Suceptible-Infectious-Removed

Quadcopter 1D	Quadcopter 2D	Dijkstra Algorithm	A-star Algorithm
Configuration Space	Potential Field Path	2D Homography	3D Homography
Optical Track	Point Cloud	Calibration	Kalman Filter
Occupancy Grid Map	Particle Localization	PD Control	PD Track Arm
Solve ODE	Estimated Kalman Filter	Mobile Inverted Pendulum	LQR MIP
PID MIP	Value Iteration	sarsa	Q-Learning
SIR model