<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper presents the development of an automated guided vehicle with omni-wheels for autonomous navigation under a robot operating system framework. Specifically, a laser rangefinder-constructed two-dimensional environment map is integrated with a three-dimensional point cloud map to achieve real-time robot positioning, using the oriented features from accelerated segment testing and a rotated binary robust independent elementary feature detector-simultaneous localization and mapping algorithm. In the path planning for autonomous navigation of the omnidirectional mobile robot, we applied the A* global path search algorithm, which uses a heuristic function to estimate the robot position difference and searches for the best direction. Moreover, we employed the time-elastic-band method for local path planning, which merges the time interval of two locations to realize time optimization for dynamic obstacle avoidance. The experimental results verified the effectiveness of the applied algorithms for the omni-wheeled mobile robot. Furthermore, the results showed a superior performance over the adaptive Monte Carlo localization for robot localization and dynamic window approach for local path planning.</p>
</abstract>

This paper presents the development of an automated guided vehicle with omni-wheels for autonomous navigation under a robot operating system framework. Specifically, a laser rangefinder-constructed two-dimensional environment map is integrated with a three-dimensional point cloud map to achieve real-time robot positioning, using the oriented features from accelerated segment testing and a rotated binary robust independent elementary feature detector-simultaneous localization and mapping algorithm. In the path planning for autonomous navigation of the omnidirectional mobile robot, we applied the A* global path search algorithm, which uses a heuristic function to estimate the robot position difference and searches for the best direction. Moreover, we employed the time-elastic-band method for local path planning, which merges the time interval of two locations to realize time optimization for dynamic obstacle avoidance. The experimental results verified the effectiveness of the applied algorithms for the omni-wheeled mobile robot. Furthermore, the results showed a superior performance over the adaptive Monte Carlo localization for robot localization and dynamic window approach for local path planning.

Development of an Omnidirectional AGV by Applying ORB-SLAM for Navigation Under ROS Framework

Journal of Automation, Mobile Robotics and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This paper presents the development of an automated guided vehicle with omni-wheels for autonomous navigation under a robot operating system framework....

Development of an Omnidirectional AGV by Applying ORB-SLAM for Navigation Under ROS Framework

Pubblicato online: 04 apr 2023

Pagine: 14 - 20

Ricevuto: 10 ott 2021

Accettato: 08 feb 2022

DOI: https://doi.org/10.14313/jamris/1-2022/2

Parole chiave
ROS, ORB-SLAM, Omnidirectional AGV, Autonomous Navigation

© 2022 Pan-Long Wu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Development of an Omnidirectional AGV by Applying ORB-SLAM for Navigation Under ROS Framework

Pubblicato online: 04 apr 2023

Pagine: 14 - 20

Ricevuto: 10 ott 2021

Accettato: 08 feb 2022

DOI: https://doi.org/10.14313/jamris/1-2022/2

Parole chiaveROS, ORB-SLAM, Omnidirectional AGV, Autonomous Navigation

© 2022 Pan-Long Wu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
ROS, ORB-SLAM, Omnidirectional AGV, Autonomous Navigation