AI Article Synopsis
- This study introduces a method for underwater drones to estimate their positions relative to each other using only visual feedback from an onboard camera and IMU data, avoiding traditional communication and sonar methods.
- The research focuses on a leader-follower control architecture that enables a group of these low-cost drones to form specific shapes while improving position predictions with an Extended Kalman Filter (EKF) when robots are out of camera view.
- The experimental validation was conducted with BlueROVs on a ROS platform in realistic scenarios, allowing for the evaluation of distributed control algorithms for these types of underwater robots.
Article Abstract
This study presents a relative localization estimation method for a group of low-cost underwater drones (l-UD), which only uses visual feedback provided by an on-board camera and IMU data. It aims to design a distributed controller for a group of robots to reach a specific shape. This controller is based on a leader-follower architecture. The main contribution is to determine the relative position between the l-UD without using digital communication and sonar positioning methods. In addition, the proposed implementation of the EKF to fuse the vision data and the IMU data improves the prediction capability in cases where the robot is out of view of the camera. This approach allows the study and testing of distributed control algorithms for low-cost underwater drones. Finally, three robot operating system (ROS) platform-based BlueROVs are used in an experiment in a near-realistic environment. The experimental validation of the approach has been obtained by investigating different scenarios.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10059849 | PMC |
| http://dx.doi.org/10.3390/s23063028 | DOI Listing |
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