dc.contributor.author |
Vartholomeos, P |
en |
dc.contributor.author |
Loizou, S |
en |
dc.contributor.author |
Thiel, M |
en |
dc.contributor.author |
Kyriakopoulos, K |
en |
dc.contributor.author |
Papadopoulos, E |
en |
dc.date.accessioned |
2014-03-01T02:43:59Z |
|
dc.date.available |
2014-03-01T02:43:59Z |
|
dc.date.issued |
2006 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/31596 |
|
dc.subject |
Collision Avoidance |
en |
dc.subject |
Control Architecture |
en |
dc.subject |
Control System |
en |
dc.subject |
Machine Learning |
en |
dc.subject |
Position Control |
en |
dc.subject |
Robot Navigation |
en |
dc.subject |
Theoretical Framework |
en |
dc.subject |
Trajectory Tracking |
en |
dc.subject.other |
Application domains |
en |
dc.subject.other |
Cell manipulation |
en |
dc.subject.other |
Centralized control architecture |
en |
dc.subject.other |
Control module |
en |
dc.subject.other |
Control system architecture |
en |
dc.subject.other |
Execution units |
en |
dc.subject.other |
Hardware experiment |
en |
dc.subject.other |
High level controllers |
en |
dc.subject.other |
High level simulation |
en |
dc.subject.other |
Low level |
en |
dc.subject.other |
Machine learning algorithms |
en |
dc.subject.other |
Micro-scale |
en |
dc.subject.other |
Multi agent |
en |
dc.subject.other |
Multi-robot navigation |
en |
dc.subject.other |
Position controller |
en |
dc.subject.other |
Robotic platforms |
en |
dc.subject.other |
Theoretical framework |
en |
dc.subject.other |
Trajectory tracking |
en |
dc.subject.other |
Control |
en |
dc.subject.other |
Learning algorithms |
en |
dc.subject.other |
Learning systems |
en |
dc.subject.other |
Multi agent systems |
en |
dc.subject.other |
Position control |
en |
dc.subject.other |
Robotics |
en |
dc.subject.other |
Robots |
en |
dc.subject.other |
Three dimensional |
en |
dc.subject.other |
Tracking (position) |
en |
dc.subject.other |
Controllers |
en |
dc.title |
Control of the multi agent micro-robotic platform miCRoN |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1109/CACSD-CCA-ISIC.2006.4776849 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/CACSD-CCA-ISIC.2006.4776849 |
en |
heal.identifier.secondary |
4776849 |
en |
heal.publicationDate |
2006 |
en |
heal.abstract |
This paper presents the theoretical framework for the centralized control architecture of the multi agent microrobotic platform MiCRoN. The entire control system architecture integrates sensory modules, modeling modules, and control modules. The latter are composed by (i) a high level simulation and autonomous execution unit that is capable for on-line multi-robot navigation with collision avoidance, (ii) a trajectory tracking unit for manipulation purposes, and (iii) a low level position controller that performs position control exploiting machine learning algorithms. The high level controllers take into account behaviors specific to the microscale. The performance of the layered control system is evaluated through simulations and preliminary hardware experiments on a micro-robotic platform. The application domain of the MiCRoN platform is cell manipulation, and 3-D assembly for micro-fabrication.©2006 IEEE. |
en |
heal.journalName |
Proceedings of the IEEE International Conference on Control Applications |
en |
dc.identifier.doi |
10.1109/CACSD-CCA-ISIC.2006.4776849 |
en |
dc.identifier.spage |
1414 |
en |
dc.identifier.epage |
1419 |
en |