- Short Description
Although robotic manipulation hardware has seen impressive advances over the last few years, humanlike dexterous manipulation capabilities still elude us. The focus of this project is to improve the manual intelligence capabilites of anthropomorphic robot hands by learning from human motor skills. To do this, experiment involving human participants grasping and manipulating daily-life objects will be conducted. Multi-modal data (i.e., kinematics, haptic and eye-tracking) will be tracked and recorded using MILAB setup and software facilities. The recorded multidimensional data will be then analysed in order to gain further insights that will drive the creation of new grasping control strategies for robots.
Team members will:
(1) Design and perform human experiment at MILAB setup
(2) Analyse the recorded data with particular focus being placed on learning a smooth transition from the grasping to the placing task
(3) Improve the currently available methods on a Shadow hand/Kuka simulation and real setup, thus endowing our robots with more natural and human like behaviour.
- Required skils
The analysis and programming will be done in C/C++ and Matlab/Python (R-statistics).
Please note that the teams will be selected by the supervisors on the basis of short applications that students are expected to send to them. Registering to the project in the ekVV will only be regarded as expression of interest; it will not secure a team membership. Please get in touch with the supervisors for information on the application procedure.
Rhythmus | Tag | Uhrzeit | Format / Ort | Zeitraum |
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Modul | Veranstaltung | Leistungen | |
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39-M-Inf-GP Grundlagenprojekt Intelligente Systeme | Gruppenprojekt | unbenotete Prüfungsleistung
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Studieninformation |
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