Abstract
In recent years, there have been significant advances in navigation methods for autonomous robotic systems, giving rise to a diverse range of navigation techniques. These techniques include GPS-based, SLAM-based, and monocular depth-based navigation. However, each of these approaches has its limitations. Typically, these techniques rely on either external sensors and positioning systems or require the creation of a local map prior to initiating navigation. This paper introduces a new approach for autonomous navigation of ground robots: mapless navigation using a pre-trained monocular depth network. This technique offers an efficient and cost-effective way of navigating without the need for a pre-existing map of the environment. To evaluate and compare the performance of our method, we conducted experiments using two different depth estimation models tested within the Gazebo simulation environment.
Originalsprog | Engelsk |
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Titel | 9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023 |
Antal sider | 6 |
Forlag | IEEE (Institute of Electrical and Electronics Engineers) |
Publikationsdato | okt. 2023 |
Sider | 1635 - 1640 |
ISBN (Trykt) | 979-8-3503-1141-9 |
ISBN (Elektronisk) | 979-8-3503-1140-2 |
DOI | |
Status | Udgivet - okt. 2023 |
Begivenhed | 9th International Conference on Control, Decision and Information Technologies (CoDIT) - Rome, Italien Varighed: 3 jul. 2023 → 6 jul. 2023 https://codit2023.com/ |
Konference
Konference | 9th International Conference on Control, Decision and Information Technologies (CoDIT) |
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Land/Område | Italien |
By | Rome |
Periode | 03/07/2023 → 06/07/2023 |
Internetadresse |
Navn | International Conference on Control, Decision and Information Technologies (CoDIT) |
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ISSN | 2576-3555 |