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most citedInterpretable Hidden Markov Model-Based Deep Reinforcement Learning Hierarchical Framework for Predictive Maintenance of Turbofan Engines

11 citations · 22 across the 7 of their papers we have counts for

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cs.RO2024★ 8 cited

TalkWithMachines: Enhancing Human-Robot Interaction for Interpretable Industrial Robotics Through Large/Vision Language Models

Ammar N. Abbas, Csaba Beleznai

TalkWithMachines aims to enhance human-robot interaction by contributing to interpretable industrial robotic systems, especially for safety-critical applications. The presented pap…

cs.RO2024

Safety-Driven Deep Reinforcement Learning Framework for Cobots: A Sim2Real Approach

Ammar N. Abbas, Shakra Mehak, Georgios C. Chasparis +4

This study presents a novel methodology incorporating safety constraints into a robotic simulation during the training of deep reinforcement learning (DRL). The framework integrate…