# SCvx

**Repository Path**: olupengo/SCvx

## Basic Information

- **Project Name**: SCvx
- **Description**: 文献Successive Convexification: A Superlinearly Convergent Algorithm for Non-convex Optimal Control Problems（by Yuanqi Mao, Michael Szmuk and Behcet Acikmese）复现Python程序
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 3
- **Forks**: 0
- **Created**: 2019-09-12
- **Last Updated**: 2024-01-05

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# SuccessiveConvexification
Implementation of [Successive Convexification: A Superlinearly Convergent Algorithm for Non-convex Optimal Control Problems
](https://arxiv.org/abs/1804.06539) 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](https://arxiv.org/abs/1802.03827)
by Michael Szmuk and Behçet Açıkmeşe.

![](https://camo.githubusercontent.com/991e3765fb75c4687b4a191b89e1f81529177b45/68747470733a2f2f692e696d6775722e636f6d2f5736453072674c2e706e67)

[Video example of generated trajectories](https://gfycat.com/InbornCoarseArcticseal)

- Differential drive robot path planning with free-final-time and non-convex obstacle constraints:
![](https://camo.githubusercontent.com/8b82a55c439d7a35e537e127f2f045eafcee9392/68747470733a2f2f692e696d6775722e636f6d2f784e61443565502e706e67)

- 2D rocket landing problem
[Feed-forward input tested in a box2d physics simulation](https://gfycat.com/DaringPortlyBlacklab)

感谢github上昵称为 Sven Niederberger 的同学，这是我从他github上拷贝过来的，网址：https://github.com/EmbersArc/SCvx