Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

[RSS2024] Official implementation of "Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation"

[T-RO 2023] DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles

Implementation of the D* lite algorithm in Python for "Improved Fast Replanning for Robot Navigation in Unknown Terrain"

Wild Visual Navigation: A system for fast traversability learning via pre-trained models and online self-supervision

Indoor segmentation for robot navigating, which is based on deeplab model in TensorFlow.

A goal-driven autonomous exploration through deep reinforcement learning (ICRA 2022) system that combines reactive and planned robot navigation in unknown environments

A curated list of robot social navigation.

Repository for the paper "Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues"

[IROS23] Hybrid Map-Based Path Planning for Robot Navigation in Unstructured Environments

This repository contains the source code for our paper: "NaviSTAR: Socially Aware Robot Navigation with Hybrid Spatio-Temporal Graph Transformer and Preference Learning". For more details, please refer to our project website at https://sites.google.com/view/san-navistar.

Pedestrian ROS simulator with Gazebo and differential wheeled robots

Simple differential drive robot for indoor environments simulated using ROS and Gazebo.

A Reinforcement Learning (RL) based navigation implementation for mobile robot navigation. Q-Learning, SARSA and Deep Q-Network algorithms were compared.

Mobile Robot Planner with Low-cost Cameras Using Deep Reinforcement Learning

Socially normative mobile robot navigation

Adaptive Risk Tendency Implicit Quantile Network for Drone Navigation under Partial Observability.

DRL-VO navigation policy for BARN Challenge

Official repository for the paper "Move Beyond Trajectories: Distribution Space Coupling for Crowd Navigation"

Deep Reinforcement Learning for mobile robot navigation in ROS2 Gazebo simulator. Using DRL (SAC, TD3) neural networks, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.