Below, you can find links for the papers, that have been published up until now, from the ESRs inside the REMARO program!
Real-Time Automatic Wall Detection and Localization based on Side Scan Sonar Images
Authors: Martin Aubard, Ana Madureira, Luis Madureira and José Pinto
Date: September 21, 2022
Accurate identification of an uncertain underwater environment is one of the challenges of underwater robotics. Autonomous Underwater Vehicle (AUV) needs to understand its environment accurately to achieve autonomous tasks. The method proposed in this paper is a real-time automatic target recognition based on Side Scan Sonar images to detect and localize a harbor’s wall. This paper explains real-time Side Scan Sonar image generation and compares three object detection algorithms (YOLOv5, YOLOv5-TR, and YOLOX) using transfer learning. The YOLOv5-TR algorithm has the most accurate detection with 99% during training, whereas the YOLOX provides the best accuracy of 91.3% for a recorded survey detection. The YOLOX algorithm realizes the flow chart validation’s real-time detection and target localization.
Belief-based fault recovery for marine robotics
Authors: Jeremy Paul Coffelt, Mahya Mohammadi Kashani, Andrzej Wąsowski and Peter Kampmann
Date: August 16, 2022
We propose a framework expanding the capabilities of underwater robots to autonomously recover from anomalous situations. The framework is built around a knowledge model developed in three stages. First, we create a deterministic knowledge base to describe the “health” of hardware, software, and environment components involved in a mission. Next, we describe the same components probabilistically, defining probabilities of failures, faults, and fixes. Finally, we combine the deterministic and probabilistic knowledge into a minimal ROS package designed to detect failures, isolate the underlying faults, propose fixes for the faults, and determine which is the most likely to help. We motivate the solution with a camera fault scenario and demonstrate it with a thruster failure on a real AUV and a simulated ROV.
Model-Based Testing for System-Level Safety of Autonomous Underwater Robots
Authors: Sergio Quijano, Mahsa Varshosaz
Date: June 08, 2022
For the deployment of autonomous robotic systems in mission- and safety-critical underwater environments, aspects such as reasoning and planning need to be designed to operate in highly dynamic, uncertain environments while assuring a safe and reliable operation. Systems are often deployed without a prior safety assessment or developed with safety analysis as a separate engineering process. In this paper, to tackle these challenges, we propose an initial research vision and plan with the envisioned contributions towards designing an approach for system-wide modeling and Model-Based Testing to support safety assessments of autonomous underwater robots.