A stable method for task priority adaptation in quadratic programming via reinforcement learning

In emerging manufacturing facilities, robots must enhance their flexibility. They are expected to perform complex jobs, showing different behaviors on the need, all within unstructured environments, and without requiring reprogramming or setup adjustments. To address this challenge, we introduce the...

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Vydáno v:	Robotics and computer-integrated manufacturing Ročník 91; s. 102857
Hlavní autoři:	Testa, Andrea, Laghi, Marco, Bianco, Edoardo Del, Raiola, Gennaro, Hoffman, Enrico Mingo, Ajoudani, Arash
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.02.2025 Elsevier
Témata:	Computer Science Machine Learning Machine learning for robot control Optimization and optimal control Reinforcement learning Robotics Machine learning for robot control Optimization and optimal control Reinforcement learning Reinforcement Learning Machine Learning for Robot Control Optimization and Optimal Control Optimization and Optimal Control Reinforcement Learning Machine Learning for Robot Control
ISSN:	0736-5845, 1879-2537
On-line přístup:	Získat plný text
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