Name
Abstract | ||
|---|---|---|
In shared human-robot environments, control systems operate based on the information about both human and robot activities to facilitate the successful collaboration between the two. This paper contributes to the emerging field of human-robot collaboration (HRC) by unifying human action recognition (HAR) and high-level robot control technique into single control system. Approach in this paper includes artificial neural network based classifier for recognition of human activity and task-based control as an example of high-level control technique. Classifier is developed based on the data from wearable sensors attached on the human arms. Recognized human activity is used as the input for the selection of functions that describe robot's activity (task). This papers combines both the theoretical approach to the task-based control and it's synergy with HAR while the developed artificial neural network classifier is experimentally validated. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IECON.2018.8591206 | IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Field | DocType | ISSN |
Robot control,Activity recognition,Task analysis,Robot kinematics,Control engineering,Artificial intelligence,Engineering,Control system,Artificial neural network,Robot,Human–robot interaction | Conference | 1553-572X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tarik Uzunovic | 1 | 2 | 3.18 |
| Edin Golubovic | 2 | 14 | 3.66 |
| Zlatan Tucakovic | 3 | 0 | 0.34 |
| Yasin Acikmese | 4 | 0 | 0.34 |
| Asif Sabanoviç | 5 | 0 | 0.34 |