ICUAS 2020 Paper Abstract

Close

Paper FrA1.5

Kulathunga, Geesara (Innopolis University), Fedorenko, Roman (Innopolis University), Klimchik, Alexandr (Innopolis University)

Regions of Interest Segmentation from LiDAR Point Cloud for Multirotor Aerial Vehicles

Scheduled for presentation during the Regular Session "Navigation" (FrA1), Friday, September 4, 2020, 10:20−10:40, Macedonia Hall

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on March 28, 2024

Keywords Navigation, Path Planning

Abstract

We propose a novel filter for segmenting the regions of interest from LiDAR 3D point cloud for multirotor aerial vehicles. It is specially targeted for real-time applications and works on sparse LiDAR point clouds without preliminary mapping. We use this filter as a crucial component of fast obstacle avoidance system for agriculture drone operating at low altitude. As the first step, each point cloud is transformed into a depth image and then identify places near to the vehicle (local maxima) by locating areas with high pixel densities. Afterwards, we merge the original depth image with identified locations after maximizing intensities of pixels in which local maxima were obtained. Next step is to calculate the range angle image that represents angles between two consecutive laser beams based on the improved depth image. Once the corresponding range angle image is constructed, smoothing is applied to reduce the noise. Finally, we find out connected components within the improved depth image while incorporating smoothed range angle image. This allows separating the regions of interest. The filter has been tested on various simulated environments as well as an actual drone and provides real-time performance. We make our source code, dataset footnote[2]{Source code and dataset are available at url{https://github.com/GPrathap/hagen.git}} and real-world experimentfootnote[3]{Real-world experiment result can be found on the following link: url{https://www.youtube.com/watch?v=iHd_ZkhKPjc}}available online.

 

 

All Content © PaperCept, Inc.

This site is protected by copyright and trademark laws under US and International law.
All rights reserved. © 2002-2024 PaperCept, Inc.
Page generated 2024-03-28  11:01:27 PST  Terms of use