[IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2)

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.

[TRO 2025] NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning.

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

A curated list of robot social navigation.

[RA-L'25 & ICRA'26] An Reliable and Efficient Framework for Zero-Shot Object Navigation

Deep Reinforcement Learning for mobile robot navigation in IR-SIM simulation. Using DRL (SAC, TD3, PPO, DDPG) neural networks, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

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

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

100+ robotics algorithms in Rust: planning, localization, SLAM, control, and benchmarks.

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.

[AAAI 2026 Oral] FreeAskWorld is an interactive simulation framework that integrates large language models (LLMs) for high-level planning and socially grounded interaction in embodied AI.

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

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

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

[RA-L '24] Learning self-supervised traversability with navigation experiences of mobile robots: A risk-aware self-training approach

Code base for SICNav T-RO paper and SICNav-Diffusion RA-L paper

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

Modular DRL framework for autonomous robot navigation in ROS2. Plug-and-play RL backends (Stable-Baselines3, DreamerV3), composable reward functions, observation spaces & neural architectures - built for research and deployment.