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...
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| Формат: | Online |
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| Язык: | английский |
| Опубликовано: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Предметы: | |
| Online-ссылка: | ONIX_20210501_9783039363384_537 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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| _version_ | 1869521070020624384 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-68791 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-687912024-03-30T12:51:07Z Machine Learning Techniques for Assistive Robotics Quevedo, Miguel Orts-Escolano, Sergio Martinez-Martin, Ester thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries 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. 2021-05-01T15:29:26Z 2021-05-01T15:29:26Z 2020 book ONIX_20210501_9783039363384_537 9783039363384 9783039363391 https://directory.doabooks.org/handle/20.500.12854/68791 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/2557 https://mdpi.com/books/pdfview/book/2557 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03936-339-1 10.3390/books978-3-03936-339-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039363384 9783039363391 210 Basel, Switzerland open access |
| spellingShingle | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Machine Learning Techniques for Assistive Robotics |
| title | Machine Learning Techniques for Assistive Robotics |
| title_full | Machine Learning Techniques for Assistive Robotics |
| title_fullStr | Machine Learning Techniques for Assistive Robotics |
| title_full_unstemmed | Machine Learning Techniques for Assistive Robotics |
| title_short | Machine Learning Techniques for Assistive Robotics |
| title_sort | machine learning techniques for assistive robotics |
| topic | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20210501_9783039363384_537 |