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Joint failures can disrupt gait coordination, velocity tracking, and body stability in quadruped robots by reducing the available control authority. This study investigates faults in which joints remain locked at fixed angles and presents Adjudicate Reconfiguration and Evolving Regularization Meta Reinforcement Learnin...
With the deepening of Industry 4.0, complex industrial processes show strong coupling, nonlinearity, and dynamic uncertainty, requiring coordinated optimization of production efficiency, quality, energy consumption, and emissions. Traditional control methods are often unable to balance conflicting objectives or adapt t...
This review examines AI-driven locomotion, including reinforcement learning, non-RL machine-learning methods, model-based approaches, and hybrid strategies, with attention to robustness, sim-to-real transfer, sensor use, computational requirements, and hardware validation, and summarizes AI-supported advanced behaviors...
Experimental results demonstrate that the integrated system improves locomotion stability, energy efficiency, and terrain adaptability compared with baseline controllers, highlighting the effectiveness of combining a structured gait prior, lightweight residual coordination, and hardware-aware deployment for practical q...
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