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:
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
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
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