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Machine Learning Techniques for Assistive Robotics
Assistive robots are categorized as robots that share their area of work and interact with humans. Their main goals are to help, assist, and monitor humans, especially people with disabilities. To achieve these goals, it is necessary that these robots possess a series of characteristics, namely the abilities to perceive their environment from their sensors and act consequently, to interact with people in a multimodal manner, and to navigate and make decisions autonomously. This complexity demands computationally expensive algorithms to be performed in real time. The advent of high-end embedded processors has enabled several such algorithms to be processed concurrently and in real time. All these capabilities involve, to a greater or less extent, the use of machine learning techniques. In particular, in the last few years, new deep learning techniques have enabled a very important qualitative leap in different problems related to perception, navigation, and human understanding. In this Special Issue, several works are presented involving the use of machine learning techniques for assistive technologies, in particular for assistive robots.
Image Processing: Concepts, Methodologies, Tools, and Applications
Advancements in digital technology continue to expand the image science field through the tools and techniques utilized to process two-dimensional images and videos. Image Processing: Concepts, Methodologies, Tools, and Applications presents a collection of research on this multidisciplinary field and the operation of multi-dimensional signals with systems that range from simple digital circuits to computers. This reference source is essential for researchers, academics, and students in the computer science, computer vision, and electrical engineering fields.
Robotics: Concepts, Methodologies, Tools, and Applications
"This book explores some of the most recent developments in robotic motion, artificial intelligence, and human-machine interaction, providing insight into a wide variety of applications and functional areas"--Provided by publisher.
Robot 2019: Fourth Iberian Robotics Conference
This book gathers a selection of papers presented at ROBOT 2019 – the Fourth Iberian Robotics Conference, held in Porto, Portugal, on November 20th–22nd, 2019. ROBOT 2019 is part of a series of conferences jointly organized by the SPR – Sociedade Portuguesa de Robótica (Portuguese Society for Robotics) and SEIDROB – Sociedad Española para la Investigación y Desarrollo en Robótica (Spanish Society for Research and Development in Robotics). ROBOT 2019 built upon several previous successful events, including three biannual workshops and the three previous installments of the Iberian Robotics Conference, and chiefly focused on presenting the latest findings and applications in robotics from the Iberian Peninsula, although the event was also open to research and researchers from other countries. The event featured five plenary talks on state-of-the-art topics and 16 special sessions, plus a main/general robotics track. In total, after a stringent review process, 112 high-quality papers written by authors from 24 countries were selected for publication.
Robotic Vision: Technologies for Machine Learning and Vision Applications
Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed. Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.
Advances in Physical Agents II
The book reports on cutting-edge Artificial Intelligence (AI) theories and methods aimed at the control and coordination of agents acting and moving in a dynamic environment. It covers a wide range of topics relating to: autonomous navigation, localization and mapping; mobile and social robots; multiagent systems; human-robot interaction; perception systems; and deep-learning techniques applied to the robotics. Based on the 21st edition of the International Workshop of Physical Agents (WAF 2020), held virtually on November 19-20, 2020, from Alcalá de Henares, Madrid, Spain, this book offers a snapshot of the state-of-the-art in the field of physical agents, with a special emphasis on novel AI techniques in perception, navigation and human robot interaction for autonomous systems.
Inteligencia artificial
ÍNDICE: Introducción. Búsqueda heurística. Representación e inferencia. Aprendizaje. Planificación y scheduling. Lenguaje natural. Visión artificial. Robótica.
