In this paper, we present the development of autonomous navigation capabilities for small
cruise boats, and their verification by field experiments in a canal and its surrounding waters …

In this paper, we present the design, development and a practical use of an Autonomous
Surface Vehicle (ASV) as a modular and flexible platform for a large variety of marine tasks …

Abstract The Deep Q-Network (DQN) is one of the key methods in the deep reinforcement
learning algorithm, which has a deep neural network structure used to estimate Q-values in …

Abstract The Deep Q-Network (DQN) is one of the deep reinforcement learning algorithms,
which uses deep neural network structure to estimate the Q-value in Q-learning. In the …

Freshwater ecosystems are vast areas that are constantly changing and evolving. To
maintain the ecosystem as well as the structures located close to bodies of water, frequent …

Abstract The Deep Q-Network (DQN) is one of the deep reinforcement learning algorithms,
which uses deep neural network structure to estimate the Q-value in Q-learning. In the …

This paper presents an optimized design of research-oriented ASVs and a systematic
design evaluation methodology for reliable in-water sensing. The objective is to minimize …

Underwater crime scene investigation and emergency response are tasks typically carried
out by divers constituting part of a specialist team. Operating in such dynamic environments …

We introduce a multisensor navigation system for autonomous surface vessels (ASVs)
intended for water-quality monitoring in freshwater lakes. Our mission planner uses satellite …

Environmental monitoring and surveying operations on rivers currently are performed
primarily with manually-operated boats. In this domain, autonomous coverage of areas is of …