MAPTOR: Multiphase Adaptive Trajectory Optimizer#
Date: Jul 15, 2025 Version: 0.2.1
Useful links: Install | Source Repository | Issues & Ideas |
MAPTOR is a Python framework for trajectory and design optimization using optimal control. MAPTOR simultaneously optimizes system parameters and trajectories for vehicles, robots, spacecraft, and other dynamic systems.
Getting Started
Get up and running with MAPTOR in 5 minutes. Learn the basic problem definition pattern and solve your first optimal control problem.
Tutorials
Comprehensive guides covering complete problem definition including design parameters, solution data access, and best practices for multiphase optimal control.
Examples Gallery
Complete, runnable examples from aerospace to robotics. Each example includes mathematical formulation and detailed implementation.
API Reference
Comprehensive reference documentation for all public classes, functions, and methods in the MAPTOR framework.
When to Use MAPTOR#
If you only need basic PATH planning (geometry-focused problems):
A*, Dijkstra, basic RRT, PRM
Fastest for obstacle avoidance without complex dynamics
If you need TRAJECTORY optimization with simple constraints:
iLQR (iterative Linear Quadratic Regulator)
ALTRO (Augmented Lagrangian Trajectory Optimizer)
Faster convergence for dynamics-heavy, constraint-light problems
Use MAPTOR for complex DESIGN + TRAJECTORY problems:
Multiple design parameters + trajectory optimization
Complex nonlinear path constraints (obstacle avoidance, state bounds)
Multiphase missions with automatic phase linking
When you need the full flexibility of direct transcription
Installation#
pip install maptor