Udacity CarND Model Predictive Control Project
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Updated
Jan 26, 2018 - C++
Udacity CarND Model Predictive Control Project
The main goal of the project is to implement in C++ Model Predictive Control to drive the vehicle around the simulator track.
Term 2, Project 10 - Udacity Self Driving Car Nanodegre
An implementation of a Model Predictive Control to drive the car around the track
🏎️ Model Predictive Control (MPC) Project using C++, Eigen, Ipopt and CppAD for the Self-Driving Car Nanodegree at Udacity
CarND Term 2 Model Predictive Control (MPC) Project
Successfully navigate a vehicle safely and smoothly through a track in simulator using MPC
CarND Term 2 Model Predictive Control (MPC) Project
Model Predictive Controller Project for the Self-driving Cars Nanodegree.
Model Predictive Control for Trajectory Tracking of Self Driving Car
This project is to use Model Predictive Control (MPC) to drive a car in a game simulator. The server provides reference waypoints (yellow line in the demo video) via websocket, and we use MPC to compute steering and throttle commands to drive the car. The solution must be robust to 100ms latency, since it might encounter in real-world application.
mpc and wbc for mini cheetah in pybullet
[Udacity] Projects for Self-Driving Cars Nanodegree by Udacity
Model predictive controller with serial port interface. Arduino <-> RPi serial communication. Developed for CMU's 24-774 ACSI course final project.
EagleMPC-ROS contains several packages to run EagleMPC within a ROS environment
Multirotor Flight System Employing Linear Quadratic Guassian Control For Mulitirotor UAVs.
EagleMPC is a model predictive control & optimal control library for unmanned aerial manipulators (UAMs)
Quadratic Programming and Model Predictive Control Based Trajectory Optimization for platoons of equipped Cooperative Adaptive Cruise Control (CACC) Vehicles
A collection of tools for path tracking control
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