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Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki
Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki
Mechanical Engineering Undergraduate Honors Theses
Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the great achievements of deep reinforcement learning in various domains including finance,medicine, healthcare, video games, robotics and computer vision.Deep neural network was started with multi-layer perceptron (1stgeneration) and developed to deep neural networks (2ndgeneration)and it is moving forward to spiking neural networks which are knownas3rdgeneration of neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically-realistic models of neurons to carry out computation. In this thesis, we first provide a comprehensive review …
A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson
A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson
Computer Science and Computer Engineering Undergraduate Honors Theses
Cooperative 3D printing is an emerging technology that aims to increase the 3D printing speed and to overcome the size limit of the printable object by having multiple mobile 3D printers (printhead-carrying mobile robots) work together on a single print job on a factory floor. It differs from traditional layer-by-layer 3D printing due to requiring multiple mobile printers to work simultaneously without interfering with each other. Therefore, a new approach for slicing a digital model and generating commands for the mobile printers is needed, which has not been discussed in literature before. We propose a chunk-by-chunk based slicer that divides …