iPlanner: Imperative Path Planning. An end-to-end learning planning framework using a novel unsupervised imperative learning approach

An Efficient Framework for Fast UAV Exploration

[ICRA 2024] A lightweight semantic scene completion network

Learning Unknown Space for Autonomous Navigation in Clustered Environment

A modern GUI client based on Tauri, designed to run in Windows, macOS and Linux for tailored proxy experience

[ICRA 2024] AGRNav: Efficient and Energy-Saving Autonomous Navigation for Air-Ground Robots in Occlusion-Prone Environments

[RA-L 2025] OMEGA: Efficient Occlusion-Aware Navigation for Air-Ground Robot in Dynamic Environments via State Space Model

EVA-planner: an EnVironmental Adaptive Gradient-based Local Planner for Quadrotors.

FAEL: Fast Autonomous Exploration for Large-Scale Environments with a Mobile Robot

You Only Plan Once: A Learning Based Quadrotor Planner

使用C++对Minimum Snap算法进行了实现，实现的结果超过了论文中给出的计算速度。并且实现了三维和二维的Minimum Snap轨迹生成算法

A General-Purpose Trajectory Optimizer for Multicopters

Leveraging Large Language Models for Visual Target Navigation

Leveraging system development and robot deployment for aerial autonomous navigation.

An efficient single/multi-agent trajectory planner for multicopters.

[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

Hybrid A Star algorithm C++ implementation

[ICRA 2023] ARiADNE: A Reinforcement learning approach using Attention-based Deep Networks for Exploration - Public code and model

Repository Containing the Code associated with the Paper: "Learning High-Speed Flight in the Wild"

(ICLR 2019) Learning Exploration Policies for Navigation

[CVPR 2022] Multi-Robot Active Mapping via Neural Bipartite Graph Matching.

This is a project about deep reinforcement learning autonomous obstacle avoidance algorithm for UAV.