Introduction to PyPose

• Get Started Tutorial
  • Sample Code of LieTensor
  • Sample code of optimizer
• LieTensor Tutorial
  • 1. Intialization
  • 2. All arguments in PyTorch are supported
  • 3. Exponential, Logarithm and Inversion Function
  • 4. Adjoint Transforms
  • 5. Grdients
  • 6. Test a Module

Dynamics

• Cartpole Tutorial
  • Preparation
  • Create parameters for cart pole trajectory
• Floquet Tutorial
  • Preparation
  • Number of time steps
• NeuralNet Tutorial
  • Preparation

IMU

• IMU Integrator Tutorial
  • 1. What is IMU integration
  • 2. Dataset Defination
  • 3. Utility Functions
  • 4. Define Parameters
  • 5. Perform Integration
• IMU Corrector Tutorial
  • 1. Dataset Defination
  • 2. Utility Functions
  • 3. Define IMU Corrector
  • 4. Define the Loss Function
  • 5. Define the Training Process
  • 6. Define the Testing Process
  • 7. Define Parameters
  • 8. Define Dataloaders
  • 9. Main Training Loop

Pose Graph Optimization

• Pose Graph Optimization Tutorial
  • Define Pose Graph
  • Define Optimizer
  • the 1st implementation: for customization and easy to extend
  • The 2nd implementation: equivalent to the 1st one, but more compact