Reference : Robotic trajectory tracking: Bio-inspired position and torque control
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Mechanical engineering
http://hdl.handle.net/10993/40015
Robotic trajectory tracking: Bio-inspired position and torque control
English
Klecker, Sophie mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Hichri, Bassem mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Plapper, Peter mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
2019
Procedia CIRP
elsevier
Yes
International
13th CIRP Conference on Intelligent Computation in Manufacturing Engineering
from 17-07-2019 to 19-07-2019
Gulf of Naples (Ischia)
Italy
[en] Trajectory tracking ; position/torque control ; parallel control ; adaptive NN ; reinforcement learning ; adaptive control ; robust control ; contact
[en] As far as complex contact-based manufacturing tasks are concerned, humans outperform machines. Indeed, conventionally controlled robotic manipulators are limited to basic applications in close to ideal circumstances. However, tedious work in hazardous environments, make some tasks unsuitable for humans. Therefore, the interest in expanding the application-areas of robots arose. This paper employs a bottom-up approach to develop robust and adaptive learning algorithms for trajectory tracking: position and torque control in the presence of uncertainties and switching constraints. The robotic manipulators mimicking the human behavior based on bio-inspired algorithms, take advantage of their know-how. Simulations and experiments validate the concept-performance.
http://hdl.handle.net/10993/40015

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