Titlebook: Deep Learning for Unmanned Systems; Anis Koubaa,Ahmad Taher Azar Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusiv

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Desk Reference for Neuroscience-based control systems are able to provide guarantees on performance specifications, while learning-based control systems through the training process can further improve performances. The goal of this chapter is to propose control design frameworks with performance guarantees on primary (i.e. safet

Essential

Desk Reference for Neuroscienceformance of the vision control system is deeply dependent on the image processing model and algorithm. Before deep learning is widely used in computer vision, the traditional image processing methods are successful in handling the low dimension information of image features, but the traditional imag

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Mammal

: Desktop Publishing am laufenden Bandrogram. Reinforcement learning is a machine learning paradigm that is widely used in autonomous robotics, since their principles are very similar. Reinforcement learning is based on how humans and animals perceive, reason and act on their environments by trial-and-error, learning which actions are b

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aphasia

altruism

https://doi.org/10.1007/978-3-642-97496-0 locking cable harnesses in palettes using nylon ties. This work is motivated by two biologically inspired approaches. The general .-. theory for trajectory tracking and a recurrent bi-layer Hopfield artificial neural networks (HANN) for visual feedback of multiple palette’s elements. Equidistant Ca

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Rechtschreibhilfe und Thesaurus,le localization algorithms. Usually, the global positioning system (GPS) and motion capture cameras are employed to provide robot swarms with absolute position data with high precision. However, such infrastructures make the robots dependent on certain areas and hence reduce robustness. Thus, robots

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Rechtschreibhilfe und Thesaurus,tilize its potential. Deep learning represents a framework capable of learning the most complex models necessary to carry out various robotic tasks. We propose to integrate deep learning and one of the fundamental robotic algorithms—visual servoing. Fully convolutional neural networks are used for s