A light-weight, Eigen-based C++ library for trajectory optimization for legged robots.
Differential Wheeled Mobile Robot - Nonlinear Model Predictive Control based on ROS
#自然语言处理#An Eigen-based, light-weight C++ Interface to Nonlinear Programming Solvers (Ipopt, Snopt)
Fastest-lap is a vehicle dynamics simulator. It can be used to understand vehicle dynamics, to learn about driving techniques, to design car prototypes, or just for fun!
A collection of work using nonlinear model predictive control (NMPC) with discrete-time control Lyapunov functions (CLFs) and control barrier functions (CBFs)
"Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function" by J. Zeng, B. Zhang and K. Sreenath https://arxiv.org/abs/2007.11718
nonlinear control optimization tool
『PythonとCasADiで学ぶモデル予測制御』 サポートサイト
#计算机科学#Type-safe modelling DSL, symbolic transformation, and code generation for solving optimization problems.
Codes for "Balancing Computation Speed and Quality: A Decentralized Motion Planning Method for Cooperative Lane Changes of Connected and Automated Vehicles"
ROS MPC trajectory tracker. Currently only supports diff-drive/skid-steering UGVs.
Nonlinear Model Predictive Control tuning using Genetic Algorithms, employed on a trajectory controller for differential drive robot
MPC pathtracking implementation with python, solved by PANOC/IPOPT
This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo packag...
A thin IPOPT wrapper for NLPModels
Fit a partial point cloud with a superquadric
This is MPC (model predictive controller) that can predict steering and throttle to drive in a simulator.
Underactuated double-pendulum (acrobot) on a cart to play with direct optimal control methods
An optimized, easy-to-use functional style motion planning library written in C++. Developed in lab with Prof. Tao Gao at UCLA.
Codes of "Cooperative Lane Change Motion Planning of Connected and Automated Vehicles: A Stepwise Computational Framework"