# Feasible Computationally Efficient Path Planning for UAV Collision Avoidance

arXiv: https://arxiv.org/abs/2002.10623 · HTML: https://mlsanity.com/paper/2002.10623/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Synthetic Aperture Sensing for Occlusion Removal with Drone Swarms](https://mlsanity.com/paper/2212.14692/) (2022)

## Abstract (arXiv)

This paper presents a robust computationally efficient real-time collision avoidance algorithm for Unmanned Aerial Vehicle (UAV), namely Memory-based Wall Following-Artificial Potential Field (MWF-APF) method. The new algorithm switches between Wall-Following Method (WFM) and Artificial Potential Field method (APF) with improved situation awareness capability. Historical trajectory is taken into account to avoid repetitive wrong decision. Furthermore, it can be effectively applied to platform with low computing capability. As an example, a quad-rotor equipped with limited number of Time-of-Flight (TOF) rangefinders is adopted to validate the effectiveness and efficiency of this algorithm. Both software simulation and physical flight test have been conducted to demonstrate the capability of the MWF-APF method in complex scenarios.