spline-trajectory-optimization

Please head over to devel branch for the code in the paper "Spline-Based Minimum-Curvature Trajectory Optimization for Autonomous Racing".

Spline-based Trajectory Optimization tool for Autonomous Racing (Indy Autonomous Challenge)

Install

1. Install SciPy, matplotlib, shapely, casadi, bezier.
2. For min curvature problem, install Julia 1.8.5+.
3. Clone this repository and install with pip install -e ..

Run

• For min curvature problem, run julia/spline_traj_opt.ipynb.
• For min time problem, copy traj_opt_double_track.yaml in spline_traj_optm/min_time_otpm/example to your workspace, and execute traj_opt_double_track.

Repository Organization

• spline_traj_optm/examples: Example inputs for the trajectory optimization (Monza)
• spline_traj_optm/models: Data classes for holding optimization information (race track, vehicle, and trajectory information)
• spline_traj_optm/optimization: Optimization functions
• spline_traj_optm/simulator: Quasi-Steady State (QSS) simulation of a given trajectory for optimal speed
• spline_traj_optm/tests: Tests for the package
• spline_traj_optm/visualization: Functions for visualization the optimization and simulation results
• julia/spline_traj_opt.ipynb: Julia notebook of the optimization notebook

Input Format

csvs for inside bound , outside bound, and center line

• 3 columns

If there is a bank angle, should be 4 columns with the fourth column as bank angle (if 3 columns bank default to zero)