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New convolutional neural network models for efficient object recognition with humanoid robots 

Aslan, S.N.; Ucar, A.; Guzelis, C. (Taylor and Francis Inc., 2021)
Humanoid robots are expected to manipulate the objects they have not previously seen in real-life environments. Hence, it is important that the robots have the object recognition capability. However, object recognition is ...
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Learning to move an object by the humanoid robots by using deep reinforcement learning 

Aslan, S.N.; Tasci, B.; Ucar, A.; Guzelis, C. (IOS Press, 2021)
This paper proposes an algorithm for learning to move the desired object by humanoid robots. In this algorithm, the semantic segmentation algorithm and Deep Reinforcement Learning (DRL) algorithms are combined. The semantic ...
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New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration 

Aslan, S.N.; Ozalp, R.; Ucar, A.; Guzelis, C. (Springer, 2021)
As the environments that human live are complex and uncontrolled, the object manipulation with humanoid robots is regarded as one of the most challenging tasks. Learning a manipulation skill from human Demonstration (LfD) ...





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Author
Aslan, S.N. (3)
Guzelis, C. (3)
Ucar, A. (3)Ozalp, R. (1)Tasci, B. (1)SubjectHumanoid robots (3)Convolution neural networks (2)DDPG (1)Deep semantic segmentation (1)DQN (1)Learning from demonstration (1)Locomotion (1)Object manipulation (1)Object recognition (1)... View MoreDate Issued2021 (3)Has File(s)
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