A Case Study on the Performance of Gazebo with Multi-core CPUs

Yang, Hai; Wang, Xuefei

doi:10.1007/978-3-319-65289-4_63

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Modeling Of Natural Environments With Gazebo1

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2018

2023

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Cited by 4 publications

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“…For example, it is employed currently in the DARPA subterranean challenge 1 . Nevertheless, it has been found that the simulation time increases linearly with the number of elements of the environment [18].…”

Section: Modeling Of Natural Environments With Gazebomentioning

confidence: 99%

Automatic Generation of Labeled 3D Point Clouds of Natural Environments with Gazebo

Sánchez

Martínez

Morales

et al. 2019

2019 IEEE International Conference on Mechatronics (ICM)

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Progress in applying supervised learning for natural scene classification is impeded by the lack of appropriate datasets for training. This paper describes the automatic generation of synthetic three-dimensional (3D) scans of natural environments with each point labelled individually with its element class. The developed software employs the robotic simulator Gazebo to obtain range and intensity measurements from a 3D laser rangefinder aboard a ground mobile robot. Precisely, the returned intensity values are used to annotate every 3D point within its corresponding class 100% error free. Several examples are provided to show the utility of the proposed approach.

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Section: Modeling Of Natural Environments With Gazebomentioning

confidence: 99%