On using human activity recognition sensors to improve the performance of collaborative mobile manipulators: Review and outlook
| Autor: | Syed M. Aiman, Nikolaos Papakostas, Aswin K Ramasubramanian |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Biometrics Mobile manipulator Computer science Wearable computer 02 engineering and technology Workspace 010501 environmental sciences 01 natural sciences Task (project management) Activity recognition 020901 industrial engineering & automation Gait (human) Human–computer interaction General Earth and Planetary Sciences Robot 0105 earth and related environmental sciences General Environmental Science |
| Zdroj: | Procedia CIRP |
| DOI: | 10.5281/zenodo.5579579 |
| Popis: | The operation of mobile manipulators in a collaborative environment needs to be adapted to the characteristics and skills of human operators. Human activity recognition, utilizing wearable sensors and vision systems, could be used to fine tune the performance of the mobile manipulator so that human operators be better assisted. The goal is to develop a sense of safety and trust between the human and the manipulator in order to improve the ergonomics of the operator within the collaborative workspace. This paper reviews the technologies that can be used for activity tracking together with gait recognition as a biometric tool. These technologies could potentially allow the mobile robotic manipulator to dynamically adapt to the motion, skills, and intentions of the human operator and to the requirements of the task in action. This paper also proposes an idea of combining a gait recognition model and activity tracking towards improving the performance of mobile collaborative robots. |
| Databáze: | OpenAIRE |
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