1.
Andrew's Notes
2.
Money Balancing Math
3.
Recipes
4.
Tenet Timelines
5.
Autonomy
5.1.
Estimation
5.1.1.
Applied Statistics for Stochastic Processes
5.1.1.1.
Bayesian Inference
5.1.2.
Filter-Based Estimation Algorithms
5.1.2.1.
The Kalman Filter (Time-Varying LQE)
5.1.2.2.
The Kinematic Filters
5.1.2.3.
The Luenberger Observer (LQE)
5.2.
Math Fundamentals
5.2.1.
3D Geometry
5.2.1.1.
Rotations Robotics Field Guide
5.2.2.
Linear Algebra
5.2.2.1.
Visualizing Matrices
5.3.
Systems Implementation
5.3.1.
Computer Simulations
5.3.1.1.
The Rotor Blade Flapping Effect
5.3.1.2.
Event-Based Collision Detection
5.3.1.3.
The Intertial Measurement Unit (IMU) Sensor
5.3.2.
Optimization Libraries
5.3.2.1.
Ceres Solver Python Tutorial (Linux)
5.3.2.2.
2D Range-Bearing Landmark Resolution with Ceres
5.4.
Search and Optimization
5.4.1.
Least-Squares Optimization
5.4.2.
Nonlinear Optimization
5.4.3.
Optimization Over Lie Groups
5.5.
Systems Theory
5.5.1.
Signals
5.5.1.1.
Algorithms in Continuous vs Discrete Time
6.
Philosophy Essays
6.1.
Realism vs Nominalism
6.2.
Thomas Aquinas on Reason and Revelation
6.3.
Aristotelian Science
Light
Rust
Coal
Navy
Ayu
Andrew's Notes
Autonomy
Estimation
Applied Statistics for Stochastic Processes
Bayesian Inference
Filter-Based Estimation Algorithms
The Kalman Filter (Time-Varying LQE)
The Kinematic Filters
The Luenberger Observer (LQE)
Math Fundamentals
3D Geometry
Rotations Robotics Field Guide
Linear Algebra
Visualizing Matrices
Systems Implementation
Computer Simulations
The Rotor Blade Flapping Effect
Event-Based Collision Detection
The Intertial Measurement Unit (IMU) Sensor
Optimization Libraries
Ceres Solver Python Tutorial (Linux)
2D Range-Bearing Landmark Resolution with Ceres
Search and Optimization
Least-Squares Optimization
Nonlinear Optimization
Optimization Over Lie Groups
Systems Theory
Signals
Algorithms in Continuous vs Discrete Time