Advances in Autonomous Underwater Robotics Based on Machine Learning

Dear Colleagues,

In recent years, the use of autonomous or semi-autonomous robots to perform underwater missions has grown rapidly. Tasks such as submersed infrastructure inspection, the monitoring of underwater plants and algae meadows or general sub-sea mapping strongly benefit from underwater robotics.

Increasing robots’ autonomy is tightly related to the use of artificial intelligence techniques. Among them, machine learning in general and deep learning in particular have shown great potential, though still few applications exist which are specifically targeted to underwater robotics.

The purpose of this Special Issue is to publish innovative research and application-oriented works related to underwater and marine robotics uses of machine learning in particular.

Papers related (but not limited) to the following topics will be taken into consideration:

• Marine and underwater sensor processing using machine learning and deep learning:
  •  Visual: Image segmentation, classification, target localization, object detection, etc.
  • Acoustic: Point cloud/raw acoustic signal segmentation and classification, target localization, etc.
• Marine and underwater localization/SLAM using machine learning and deep learning:
  • Single-robot loop detection.
  • Multi-session and multi-robot loop detection.
  • Place/scene recognition.
  • SLAM, localization and mapping.
• Marine and underwater navigation using machine learning and deep learning:
  • Intelligent and adaptive control architectures.
  • Bio-inspired control architectures.

Papers investigating other artificial intelligence fields not necessarily related to machine or deep learning can also be taken into consideration.

Prof. Dr. Antoni Burguera
Dr. Francisco Bonin-Font
Guest Editors

Manuscript Submission Information

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