SuccessiveConvexification

Implementation of Successive Convexification: A Superlinearly Convergent Algorithm for Non-convex Optimal Control Problems by Yuanqi Mao, Michael Szmuk and Behcet Acikmese

Reqires matplotlib, numpy, scipy and cvxpy.

This framework provides an easy way to implement your own models.

Fixed- and free-final-time optimization is possible.

The following models are currently implemented:

• Rocket trajectory model with free-final-time based on Successive Convexification for 6-DoF Mars Rocket Powered Landing with Free-Final-Time by Michael Szmuk and Behçet Açıkmeşe.

Video example of generated trajectories

• Differential drive robot path planning with free-final-time and non-convex obstacle constraints:

• 2D rocket landing problem Feed-forward input tested in a box2d physics simulation