Motion planning and control package for robot navigation. C++ optimized implementations for core algorithms along with Python wrappers.
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Updated
Oct 1, 2024 - Python
Motion planning and control package for robot navigation. C++ optimized implementations for core algorithms along with Python wrappers.
A Python unmanned aircraft simulator based on the book Small Unmanned Aircraft: Theory and Practice, by Randy Beard and Tim McLain.
This Mathematica notebook provides development of a Forward Kinematic model, Inverse Kinematic Model, and Dynamic model using Generalized Momenta method of a Universal Omni Wheeled mobile robot. Also, a PID trajectory tracking controller was developed to track different trajectories with very small error.
A complete Mathematica notebook which shows derivation of Kinematics, Dynamics, and PID Trajectory Tracking Controller for a 7 DOF robotic manipulator.
BoundMPC: Cartesian Path Following with Error Bounds based on Model Predictive Control in the Joint Space
gaussian process examples
Path Planning Using AStar Algorithm
A lidar-based Teach-and-Repeat framework designed to enable outdoor autonomous navigation in harsh weather.
GPS Navigation package. Provides planner and a follow pose for a pure pursuit based controller.
25 path-tracking algorithms are (goint to be) implemented with python.
Mixed Reality based Autonoous Navigation of the UAVs
Unmanned Naval Vehicle Graduation Project
A path following differential drive robot controlled using a PID controller and Model Predictive Controller (MPC)
A robot car with a meccanum drivetrain. Also includes a radio controller
Written by Brian Lesko, the repository contains Matlab scripts demonstrating vehicle control theories largely originating or inspired from Vehicle System Controls 8832 at Ohio State
WIP Visualization of the Pure Pursuit path following algorithm
Paper: A review of path following control strategies for autonomous robotic vehicles: theory, simulations, and experiments
Autonomous path following (Pure Pursuit/Ramsete) using Quintic Hermite splines and trapezoidal motion profiles.
C++ SDL AI Steering Behaviors: Seek, Flee, Arrive, Pursue, Evade, Wander, Path Following, Collision Avoidance and Combining them.
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