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.
Original language | English |
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Title of host publication | 9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023 |
Number of pages | 6 |
Publisher | IEEE |
Publication date | Oct 2023 |
Pages | 1635 - 1640 |
ISBN (Print) | 979-8-3503-1141-9 |
ISBN (Electronic) | 979-8-3503-1140-2 |
DOIs | |
Publication status | Published - Oct 2023 |
Event | 9th International Conference on Control, Decision and Information Technologies (CoDIT) - Rome, Italy Duration: 3 Jul 2023 → 6 Jul 2023 https://codit2023.com/ |
Conference
Conference | 9th International Conference on Control, Decision and Information Technologies (CoDIT) |
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Country/Territory | Italy |
City | Rome |
Period | 03/07/2023 → 06/07/2023 |
Internet address |
Series | International Conference on Control, Decision and Information Technologies (CoDIT) |
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ISSN | 2576-3555 |