Abstract
OctoMap is an efficient probabilistic mapping framework to build occupancy maps from point clouds, representing 3D environments with cubic nodes in the octree. However, the map update policy in OctoMap has limitations. All the nodes containing points will be assigned with the same probability regardless of the points being noise, and the probability of one such node can only be increased with a single measurement. In addition, potentially occupied nodes with points inside but traversed by rays cast from the sensor to endpoints will be marked as free. To overcome these limitations in OctoMap, the current work presents a mapping method using the context of neighbouring points to update nodes containing points, with occupancy information of a point represented by the average distance from a point to its k-Nearest Neighbours. A relationship between the distance and the change in probability is defined with the Cumulative Density Function of average distances, potentially decreasing the probability of a node despite points being present inside. Experiments are conducted on 20 data sets to compare the proposed method with OctoMap. Results show that our method can achieve up to 10% improvement over the optimal performance of OctoMap.
Original language | English |
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Article number | 139 |
Journal | Sensors (Basel, Switzerland) |
Volume | 22 |
Issue number | 1 |
DOIs | |
Publication status | Published - 26 Dec 2021 |
Bibliographical note
Funding Information:Funding: This research was funded by the University of Bath grant, the University Research Studentship Award-Engineering, and the China Scholarship Council grant No. 201706120022. The APC was funded by the Bath Open Access fund.
Funding
Funding: This research was funded by the University of Bath grant, the University Research Studentship Award-Engineering, and the China Scholarship Council grant No. 201706120022. The APC was funded by the Bath Open Access fund.
Keywords
- Data sets for SLAM
- Mapping
- SLAM
ASJC Scopus subject areas
- Analytical Chemistry
- Information Systems
- Atomic and Molecular Physics, and Optics
- Biochemistry
- Instrumentation
- Electrical and Electronic Engineering
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Dataset for "Parameter Reduction and Optimisation for Point Cloud and Occupancy Mapping Algorithms"
Miao, Y. (Creator), Hunter, A. (Creator) & Georgilas, I. (Creator), University of Bath, 14 Jun 2021
DOI: 10.15125/BATH-00594
Dataset