Stars
Lightweight LiDAR-Inertial SLAM system for ROS 2. A minimal, dependency-free implementation for research and education.
Python sample codes and documents about Autonomous vehicle control algorithm. This project can be used as a technical guide book to study the algorithms and the software architectures for beginners.
A ROS 2 package for advanced robotics with the Otter USV from Maritime Robotics
A media-friendly presentation package for LaTeX
The Python Vehicle Simulator is software that supplements the textbook "Handbook of Marine Craft Hydrodynamics and Motion Control," 2nd Edition, by T. I. Fossen, published in 2021 by John Wiley & S…
Raspberry Pi Pico (RP2040) and micro-ROS integration
ROS 2 driver package for Boston Dynamics' Spot
A minimalist environment for decision-making in autonomous driving
A useful collection of CPP and PYTHON examples to learn ROS2 from zero
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…
micro-ROS library for Platform.IO
A package for the sparse identification of nonlinear dynamical systems from data
A Python library that implements GPR and GPR-STML.
Robot (Hardware) packages for the Clearpath Husky
Figure sizes, font sizes, fonts, and more configurations at minimal overhead. Fix your journal papers, conference proceedings, and other scientific publications.
Learning Lyapunov functions and control policies of nonlinear dynamical systems
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
UMich 500-Level Mobile Robotics Course
neural networks to learn Koopman eigenfunctions
A ROS package that simulates a two-dimensional robot and its sensors.
Python code for "Multivariable Feedback Control"
The Python Control Systems Library is a Python module that implements basic operations for analysis and design of feedback control systems.
A Smooth Representation of SO(3) for Deep Rotation Learning with Uncertainty.