# Design and Flight Demonstration of a Quadrotor for Urban Mapping and Target Tracking Research

arXiv: https://arxiv.org/abs/2402.13195 · HTML: https://mlsanity.com/paper/2402.13195/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 17 references that are in the map.
- First posted on arXiv 20 Feb 2024.

## Builds on (most cited first, 5 of 5)

- [Direct Sparse Odometry](https://mlsanity.com/paper/1607.02565/) (2016)
- [EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras](https://mlsanity.com/paper/1906.02919/) (2019)
- [An Autonomous Drone for Search and Rescue in Forests using Airborne Optical Sectioning](https://mlsanity.com/paper/2105.04328/) (2021)
- [PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments](https://mlsanity.com/paper/2103.06372/) (2021)
- [Autonomous Execution of Cinematographic Shots with Multiple Drones](https://mlsanity.com/paper/2006.12163/) (2020)

## Abstract (arXiv)

This paper describes the hardware design and flight demonstration of a small quadrotor with imaging sensors for urban mapping, hazard avoidance, and target tracking research. The vehicle is equipped with five cameras, including two pairs of fisheye stereo cameras that enable a nearly omnidirectional view and a two-axis gimbaled camera. An onboard NVIDIA Jetson Orin Nano computer running the Robot Operating System software is used for data collection. An autonomous tracking behavior was implemented to coordinate the motion of the quadrotor and gimbaled camera to track a moving GPS coordinate. The data collection system was demonstrated through a flight test that tracked a moving GPS-tagged vehicle through a series of roads and parking lots. A map of the environment was reconstructed from the collected images using the Direct Sparse Odometry (DSO) algorithm. The performance of the quadrotor was also characterized by acoustic noise, communication range, battery voltage in hover, and maximum speed tests.