# Research on an Autonomous UAV Search and Rescue System Based on the Improved

arXiv: https://arxiv.org/abs/2406.00504 · HTML: https://mlsanity.com/paper/2406.00504/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 16 references that are in the map.
- First posted on arXiv 1 Jun 2024.

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

- [Deformable DETR: Deformable Transformers for End-to-End Object Detection](https://mlsanity.com/paper/2010.04159/) (2020)
- [DETRs Beat YOLOs on Real-time Object Detection](https://mlsanity.com/paper/2304.08069/) (2023)
- [EGO-Planner: An ESDF-free Gradient-based Local Planner for Quadrotors](https://mlsanity.com/paper/2008.08835/) (2020)
- [Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight](https://mlsanity.com/paper/1907.01531/) (2019)
- [Differential Flatness of Lifting-Wing Quadcopters Subject to Drag and Lift for Accurate Tracking](https://mlsanity.com/paper/2212.12867/) (2022)

## Abstract (arXiv)

The demand is to solve the issue of UAV (unmanned aerial vehicle) operating autonomously and implementing practical functions such as search and rescue in complex unknown environments. This paper proposes an autonomous search and rescue UAV system based on an EGO-Planner algorithm, which is improved by innovative UAV body application and takes the methods of inverse motor backstepping to enhance the overall flight efficiency of the UAV and miniaturization of the whole machine. At the same time, the system introduced the EGO-Planner planning tool, which is optimized by a bidirectional A* algorithm along with an object detection algorithm. It solves the issue of intelligent obstacle avoidance and search and rescue. Through the simulation and field verification work, and compared with traditional algorithms, this method shows more efficiency and reliability in the task. In addition, due to the existing algorithm's improved robustness, this application shows good prospection.