A K-nearest neighbours based inverse sensor model for occupancy mapping

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

OctoMap is a popular 3D mapping framework which can model the data consistently and keep the 3D models compact with the octree. However, the occupancy map derived by OctoMap can be incorrect when the input point clouds are with noisy measurements. Point cloud filters can reduce the noisy data, but it is unreasonable to apply filters in a sparse point cloud. In this paper, we present a k-nearest neighbours (k-NN) based inverse sensor model for occupancy mapping. This method represents the occupancy information of one point with the average distance from the point to its k-NN in the point cloud. The average distances derived by all the points and their corresponding k-NN are assumed to be normally distributed. Our inverse sensor model is presented based on this normal distribution. The proposed approach is able to deal with sparse and noisy point clouds. We implement the model in the OctoMap to carry out experiments in the real environment. The experimental results show that the 3D occupancy map generated by our approach is more reliable than that generated by the inverse sensor model in OctoMap.

Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings
EditorsKaspar Althoefer, Jelizaveta Konstantinova, Ketao Zhang
PublisherSpringer Verlag
Pages75-86
Number of pages12
ISBN (Print)9783030253318
DOIs
Publication statusE-pub ahead of print - 17 Jul 2019
Event20th Towards Autonomous Robotic Systems Conference, TAROS 2019 - London, UK United Kingdom
Duration: 3 Jul 20195 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11650 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Towards Autonomous Robotic Systems Conference, TAROS 2019
CountryUK United Kingdom
CityLondon
Period3/07/195/07/19

Keywords

  • Inverse sensor model
  • K-nearest neighbours
  • Occupancy mapping

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Miao, Y., Georgilas, I., & Hunter, A. (2019). A K-nearest neighbours based inverse sensor model for occupancy mapping. In K. Althoefer, J. Konstantinova, & K. Zhang (Eds.), Towards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings (pp. 75-86). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11650 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-25332-5_7