# An Open-Source System for Vision-Based Micro-Aerial Vehicle Mapping, Planning, and Flight in Cluttered Environments

## TL;DR

This paper introduces an open-source vision-based MAV system capable of dense mapping, safe planning, and navigation in cluttered environments, validated through real-world and simulated experiments.

## Contribution

It presents a comprehensive open-source MAV system with novel integration of dense mapping and planning tailored for cluttered environments.

## Key findings

- Effective global planning and path smoothing in real-world scenarios
- Successful navigation in highly cluttered synthetic environments
- Validated system performance in search and rescue and industrial tasks

## Abstract

We present an open-source system for Micro-Aerial Vehicle autonomous navigation from vision-based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field of view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real-world scenarios are presented. We focus our experiments on evaluating global planning, path smoothing, and local planning methods on real maps made on MAVs in realistic search and rescue and industrial inspection scenarios. We also perform thousands of simulations in cluttered synthetic environments, and finally validate the complete system in real-world experiments.