# Point cloud obstacle detection with the map filtration

arXiv: https://arxiv.org/abs/2404.07730 · HTML: https://mlsanity.com/paper/2404.07730/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2024.

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

- [Recognizing and Reconstructing a Multi-Unit Floor Plan](https://mlsanity.com/paper/2408.01526/) (2024)

## Abstract (arXiv)

Obstacle detection is one of the basic tasks of a robot movement in an unknown environment. The use of a LiDAR (Light Detection And Ranging) sensor allows one to obtain a point cloud in the vicinity of the sensor. After processing this data, obstacles can be found and recorded on a map. For this task, I present a pipeline capable of detecting obstacles even on a computationally limited device. The pipeline was also tested on a real robot and qualitatively evaluated on a dataset, which was collected in Brno University of Technology lab. Time consumption was recorded and compared with 3D object detectors.