A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications
Modern robots are complex heterogeneous systems composed of different Processing Elements (PEs) with multiple sensors and actuators. This implies that different experts are needed to build such systems. Traditionally, robots included Central Processing Units (CPUs) as their PE. However, this has bee...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10138390/ |
| _version_ | 1797809174091923456 |
|---|---|
| author | Ariel Podlubne Diana Gohringer |
| author_facet | Ariel Podlubne Diana Gohringer |
| author_sort | Ariel Podlubne |
| collection | DOAJ |
| description | Modern robots are complex heterogeneous systems composed of different Processing Elements (PEs) with multiple sensors and actuators. This implies that different experts are needed to build such systems. Traditionally, robots included Central Processing Units (CPUs) as their PE. However, this has been changing over the last decade as different PEs, namely Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), have drawn the attention of roboticists. The research community focused on various techniques, methodologies, and applications separately, making integration aspects highly complex. Models, as abstractions, have been proposed to aid in designing complex systems that can also help with integration. Hence, three complementary goals are discussed in this work. The first is which robotic applications benefit from parallelizable and energy-efficient devices such as GPUs and FPGAs. The second one is to understand the contributions of different model-based approaches. Lastly, how these two can complement each other to bring benefits from one field onto the other so hardware developers, as well as roboticists, can improve the design of state-of-the-art robotic platforms. |
| first_indexed | 2024-03-13T06:48:33Z |
| format | Article |
| id | doaj.art-8f9faff3de414f16be3dcb5a54f7b0dc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T06:48:33Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8f9faff3de414f16be3dcb5a54f7b0dc2023-06-07T23:00:25ZengIEEEIEEE Access2169-35362023-01-0111538305384910.1109/ACCESS.2023.328119010138390A Survey on Adaptive Computing in Robotics: Modelling, Methods and ApplicationsAriel Podlubne0https://orcid.org/0000-0002-6868-7414Diana Gohringer1https://orcid.org/0000-0003-2571-8441Chair of Adaptive Dynamic Systems, Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden (TUD), Dresden, GermanyChair of Adaptive Dynamic Systems, Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden (TUD), Dresden, GermanyModern robots are complex heterogeneous systems composed of different Processing Elements (PEs) with multiple sensors and actuators. This implies that different experts are needed to build such systems. Traditionally, robots included Central Processing Units (CPUs) as their PE. However, this has been changing over the last decade as different PEs, namely Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), have drawn the attention of roboticists. The research community focused on various techniques, methodologies, and applications separately, making integration aspects highly complex. Models, as abstractions, have been proposed to aid in designing complex systems that can also help with integration. Hence, three complementary goals are discussed in this work. The first is which robotic applications benefit from parallelizable and energy-efficient devices such as GPUs and FPGAs. The second one is to understand the contributions of different model-based approaches. Lastly, how these two can complement each other to bring benefits from one field onto the other so hardware developers, as well as roboticists, can improve the design of state-of-the-art robotic platforms.https://ieeexplore.ieee.org/document/10138390/Model-driven engineering (MDE)roboticsfield programmable gate arrays (FPGAs)graphics processing units (GPUs) |
| spellingShingle | Ariel Podlubne Diana Gohringer A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications IEEE Access Model-driven engineering (MDE) robotics field programmable gate arrays (FPGAs) graphics processing units (GPUs) |
| title | A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications |
| title_full | A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications |
| title_fullStr | A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications |
| title_full_unstemmed | A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications |
| title_short | A Survey on Adaptive Computing in Robotics: Modelling, Methods and Applications |
| title_sort | survey on adaptive computing in robotics modelling methods and applications |
| topic | Model-driven engineering (MDE) robotics field programmable gate arrays (FPGAs) graphics processing units (GPUs) |
| url | https://ieeexplore.ieee.org/document/10138390/ |
| work_keys_str_mv | AT arielpodlubne asurveyonadaptivecomputinginroboticsmodellingmethodsandapplications AT dianagohringer asurveyonadaptivecomputinginroboticsmodellingmethodsandapplications AT arielpodlubne surveyonadaptivecomputinginroboticsmodellingmethodsandapplications AT dianagohringer surveyonadaptivecomputinginroboticsmodellingmethodsandapplications |