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ADAM implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.
Planning and control for autonomous racing vehicles
This Python script performs a Model Predictive Control (MPC) simulation for vehicle lateral control using the CasADi framework. The main objective of this script is to compute optimal controls for a given vehicle's model while considering several constraints.
Bsed on the CasADi original paper: "CasADi: a software framework for nonlinear optimization and optimal control"
This repository is an implementation of the work from Mohamed W. Mehrez. I convert the original code in MATLAB to the Python
Safe control of unknown dynamic systems with reinforcement learning and model predictive control
Implementations of Control (PID, LQ, MPC, ...) and AI (fuzzy logic, Q-learner, SARSA, ...) algorithms
RNN based on Chandler Zuo's implementation of the paper: A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction
A reliable controller is critical for execution of safe and smooth maneuvers of an autonomous vehicle. The controller must be robust to external disturbances, such as road surface, weather, wind conditions, and so on. It also needs to deal with internal variations of vehicle sub-systems, including powertrain inefficiency, measurement errors, time delay, etc. These factors introduce issues in controller performance. In this paper, a feed-forward compensator is designed via a data-driven method to model and optimize the controller’s performance. Principal Component Analysis (PCA) is applied for extracting influential features, after which a Time Delay Neural Network is adopted to predict control errors over a future time horizon. Based on the predicted error, a feedforward compensator is then designed to improve control performance. Simulation results in different scenarios show that, with the help of with the proposed feedforward compensator, the maximum path tracking error and the steering wheel angle oscillation are improved by 44.4% and 26.7%, respectively.
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
This repo is related to UAV Confrontation using Heirarchial MultiAgent Reinforcement Learning
Projects_Demonstrations
Master's thesis about Deep Reinforcement Learning for Decision Making in autonomous driving
An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).
Experiment Codes for the paper "An Efficient and Effective Second-Order Training Algorithm For LSTM-based Adaptive Learning"
Implement backpropagation and extended kalman filter to train feedforward neural networks.
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
Project for the course "Statistical Learning and Stochastic Control" at University of Stuttgart
MPC with Gaussian Process
Policy Search for Model Predictive Control with Application to Agile Drone Flight
HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems
CasADi implementation of the iterative linear quadratic regulator
Code for the paper, "Industrial, large-scale model predictive control with structured neural networks."
Learning to race challenge for 2020 workshop
Use PyTorch Models with CasADi and Acados
learning-based model predictive control
learning-based model predictive control of autonomous driving
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.