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pandorathanator's Projects

anti-windup-compensator icon anti-windup-compensator

List of additional files available for the interested reader of "Vibration Control Subjected to Windup Problem: An Applied View on Analysis and Synthesis with Convex Formulation"

auto-drift icon auto-drift

Autonomously drifting car that learned how to drift in a roundabout using Deep Reinforcement Learning and the Carla Simulator. Performed as part of a project in the course TSFS12: Autonomous vehicles -- planning, control, and learning systems, taught at Linköping University.

disturbancefittingsimulink icon disturbancefittingsimulink

Code for the paper Feedforward Tuning by Fitting Iterative Learning Control Signal for Precision Motion Systems

gaas icon gaas

Open source autonomy flight and operation control system. Designed for autonomous drone and self-flying car(VTOL).

gvins icon gvins

Tightly coupled GNSS-Visual-Inertial system for locally smooth and globally consistent state estimation in complex environment.

imu_utils icon imu_utils

A ROS package tool to analyze the IMU performance.

invariant-ekf icon invariant-ekf

C++ library to implement invariant extended Kalman filtering for aided inertial navigation.

julia-robotics-paper-code icon julia-robotics-paper-code

Code associated with the paper "Julia for Robotics: Simulation and Real-time Control in a High-level Programming Language"

kalibr icon kalibr

The Kalibr visual-inertial calibration toolbox

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

《学习卡尔曼与贝叶斯滤波器——基于Python实践》 这是一本循序渐进、内容详实、实例丰富的互动式卡尔曼教程,极其适合基础浅薄的初学者! 仍在翻译中......

linuxcnc icon linuxcnc

LinuxCNC controls CNC machines. It can drive milling machines, lathes, 3d printers, laser cutters, plasma cutters, robot arms, hexapods, and more.

modernrobotics icon modernrobotics

Modern Robotics: Mechanics, Planning, and Control Code Library --- The primary purpose of the provided software is to be easy to read and educational, reinforcing the concepts in the book. The code is optimized neither for efficiency nor robustness.

mpc-and-mhe-implementation-in-matlab-using-casadi icon mpc-and-mhe-implementation-in-matlab-using-casadi

This is a workshop on implementing model predictive control (MPC) and moving horizon estimation (MHE) on Matlab. The implementation is based on the Casadi Package which is used for numerical optimization. A non-holonomic mobile robot is used as a system for the implementation. The workshop video recording can be found here https://www.youtube.com/playlist?list=PLK8squHT_Uzej3UCUHjtOtm5X7pMFSgAL ... Casadi can be downloaded here https://web.casadi.org/

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