There are 22 repositories under autonomous-navigation topic.
Python sample codes and textbook for robotics algorithms.
A Robust and Efficient Trajectory Planner for Quadrotors
An Efficient Framework for Fast UAV Exploration
Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments
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.
KR (KumarRobotics) autonomous flight system for GPS-denied quadrotors
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.
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.
APACE: Agile and Perception-aware Trajectory Generation for Quadrotor Flights (ICRA2024)
WaSR Segmentation Network for Unmanned Surface Vehicles v0.5
This is the official repository of the PIC4rl-gym presented in the paper https://ieeexplore.ieee.org/abstract/document/10193996 (Accepted at ICCCR 2023).
Final year project, autonomus indoor drone developed in ROS using DWM1001 dev-board
An all-weather, day-and-night, collision avoidance simulator that can be implemented as a digital twin for the autonomous COLREG-compliant navigation of maritime vessels.
This work proposes an anytime iterative system to concurrently solve the multi-objective path planning problem and determine the visiting order of destinations. The paper has been uploaded to arXiv at https://arxiv.org/abs/2205.14853
RosNav-RL: A flexible, modular framework for building, training, and deploying reinforcement learning navigation agents in ROS. Supports multiple RL backends with ready-to-use components for rapid development and experimentation in autonomous robot navigation.
Local Planner for ROS2
Code for our paper "Autonomous Navigation in Unknown Environments with Sparse Bayesian Kernel-based Occupancy Mapping".
Autonomous Exploration, Construction and Update of Semantic Map in real-time
[ICRA 2022] Learning to Navigate Intersections with Unsupervised Driver Trait Inference
NUS ME5413 Autonomous Mobile Robotics Planning Project
A full simulation of a warehouse autonomous mobile robot that handles Orders and performing picking and delivery Products in a warehouse in Gazebo simulator.
Nautical Object Detection using Detectron2 for Instance Segmentation Trained on Nautical Objects (buoys, ships and land).