3 citations · 4 across the 21 of their papers we have counts for
8 papers · 1 filter
A Collaborative Reasoning Framework for Anomaly Diagnostics in Underwater Robotics
Markus Buchholz, Niamh Ellis, Rahaf Abu Hara +2
The safe deployment of autonomous systems in safety-critical settings requires a paradigm that combines human expertise with AI-driven analysis, especially when anomalies are unfor…
Framework for Robust Motion Planning of Tethered Multi-Robot Systems in Marine Environments
Markus Buchholz, Ignacio Carlucho, Zebin Huang +4
This paper introduces CoralGuide, a novel framework designed for path planning and trajectory optimization for tethered multi-robot systems. We focus on marine robotics, which comm…
Tethered Multi-Robot Systems in Marine Environments
Markus Buchholz, Ignacio Carlucho, Michele Grimaldi +1
This paper introduces a novel simulation framework for evaluating motion control in tethered multi-robot systems within dynamic marine environments. Specifically, it focuses on the…
Distributed AI Agents for Cognitive Underwater Robot Autonomy
Markus Buchholz, Ignacio Carlucho, Michele Grimaldi +1
Achieving robust cognitive autonomy in robots navigating complex, unpredictable environments remains a fundamental challenge in robotics. This paper presents Underwater Robot Self-…
Advancing Shared and Multi-Agent Autonomy in Underwater Missions: Integrating Knowledge Graphs and Retrieval-Augmented Generation
Michele Grimaldi, Carlo Cernicchiaro, Sebastian Realpe Rua +6
Robotic platforms have become essential for marine operations by providing regular and continuous access to offshore assets, such as underwater infrastructure inspection, environme…
Context-Aware Behavior Learning with Heuristic Motion Memory for Underwater Manipulation
Markus Buchholz, Ignacio Carlucho, Michele Grimaldi +2
Autonomous motion planning is critical for efficient and safe underwater manipulation in dynamic marine environments. Current motion planning methods often fail to effectively util…
MarineGym: A High-Performance Reinforcement Learning Platform for Underwater Robotics
Shuguang Chu, Zebin Huang, Yutong Li +4
This work presents the MarineGym, a high-performance reinforcement learning (RL) platform specifically designed for underwater robotics. It aims to address the limitations of exist…
Stonefish: Supporting Machine Learning Research in Marine Robotics
Michele Grimaldi, Patryk Cieslak, Eduardo Ochoa +6
Simulations are highly valuable in marine robotics, offering a cost-effective and controlled environment for testing in the challenging conditions of underwater and surface operati…