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2022 IEEE ANDESCON: Technology and Innovation for Andean Industry, ANDESCON 2022(1)
Applied Intelligence(1)
International Conference on ICT Convergence(1)
Sensors(1)
Natural object manipulation using anthropomorphic robotic hand through deep reinforcement learning and deep grasping probability network
ArticleAbstract: Human hands can perform complex manipulation of various objects. It is beneficial if anthropomorphicPalabras claves:Anthropomorphic robotic hand, Deep grasping probability network, Deep reinforcement learning, Human grasping hand poses, Natural object grasping and relocation, Natural policy gradientAutores:Al-Antari M.A., Edwin Valarezo Anazco, Kim T.S., Oh J., Park N., Rivera Lopez P., Ryu G.Fuentes:googlescopusObject manipulation with an anthropomorphic robotic hand via deep reinforcement learning with a synergy space of natural hand poses
ArticleAbstract: Anthropomorphic robotic hands are designed to attain dexterous movements and flexibility much like hPalabras claves:Anthropomorphic robotic hand, Deep reinforcement learning, Natural hand poses, Object grasping, Object relocation, Synergy spaceAutores:Edwin Valarezo Anazco, Kim T.S., Rivera P.Fuentes:googlescopusReward Shaping to Learn Natural Object Manipulation With an Anthropomorphic Robotic Hand and Hand Pose Priors via On-Policy Reinforcement Learning
Conference ObjectAbstract: A key challenge in reinforcement learning (RL) for robot manipulation is to provide a reward functioPalabras claves:Anthropomorphic robotic hand, Deep reinforcement learning, Hand Poses Priors, object manipulationAutores:Edwin Valarezo Anazco, Jeong J.G., Jung H., Kim T.S., Lee J.H., Oh J., Rivera P., Ryu G.Fuentes:googlescopusSupervised Machine Learning Applied to Non-Invasive EMG Signal Classification for an Anthropomorphic Robotic Hand
Conference ObjectAbstract: Advances in hardware development have created robotic hands able to mimic the appearance and functioPalabras claves:Anthropomorphic robotic hand, Artificial Neural Network, EMG Data Classification, EMG Machine LearningAutores:Alexander Saravia-Avila, Bolivar Nunez-Montoya, Edwin Valarezo Anazco, Efrain Teran, Francis R. Loayza, Mauricio Valarezo AnazcoFuentes:scopus