autonomous-navigation

Python sample codes and textbook for robotics algorithms.

A Robust and Efficient Trajectory Planner for Quadrotors

An Efficient Framework for Fast UAV Exploration

3D Trajectory Planner in Unknown Environments

Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments

KR (KumarRobotics) autonomous flight system for GPS-denied quadrotors

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.

Header-only C++ library for robotics, control, and path planning algorithms. Work in progress, contributions are welcome!

Simulation of path planning for self-driving vehicles in Unity. This is also an implementation of the Hybrid A* pathfinding algorithm which is useful if you are interested in pathfinding for vehicles.

Autonomous Navigation of UAV using Reinforcement Learning algorithms.

An autonomous vehicle written in python

This repository intends to enable autonomous drone delivery with the Intel Aero RTF drone and PX4 autopilot. The code can be executed both on the real drone or simulated on a PC using Gazebo. Its core is a robot operating system (ROS) node, which communicates with the PX4 autopilot through mavros. It uses SVO 2.0 for visual odometry, WhyCon for visual marker localization and Ewok for trajectoy planning with collision avoidance.

All Terrain Autonomous Quadruped

A tightly coupled and real time LiDAR-Inertial SLAM algorithm. Based upon LIMO-Velo and FAST_LIO projects.

Autonomous navigation for blind people

ROS tutorial by Purdue SMART lab: Gazebo simulation - autonomous mobile robot navigation and creating custom robots and sensor plugins

A robust UAV local planner based on the ICRA2020 paper: Robust Real-time UAV Replanning Using Guided Gradient-based Optimization and Topological Paths

NUS ME5413 Autonomous Mobile Robotics Final Project

UG Project 2019-20.

This package provides a CLF-based reactive planning system, described in paper: Efficient Anytime CLF Reactive Planning System for a Bipedal Robot on Undulating Terrain. The reactive planning system consists of a 5-Hz planning thread to guide a robot to a distant goal and a 300-Hz Control-Lyapunov-Function-based (CLF-based) reactive thread to cope with robot deviations. The planning system allowed Cassie Blue to autonomously traverse sinusoidally varying terrain. More experiments are still being conducted and this repo and the paper will be updated accordingly.