| Reference : T-S Fuzzy Contact State Recognition for Compliant Motion Robotic Tasks Using Gravitat... |
| Scientific congresses, symposiums and conference proceedings : Paper published in a book | |||
| Engineering, computing & technology : Mechanical engineering | |||
| http://hdl.handle.net/10993/7635 | |||
| T-S Fuzzy Contact State Recognition for Compliant Motion Robotic Tasks Using Gravitational Search-Based Clustering Algorithm | |
| English | |
Jasim, Ibrahim  [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >] | |
| Plapper, Peter [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >] | |
| Jul-2013 | |
| 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013) | |
| Yes | |
| No | |
| International | |
| 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013) | |
| 07-07-2013 to 10-07-2013 | |
| Hyderabad | |
| India | |
| [en] Compliant motion robots ; Contact state ; Fuzzy clustering ; Gravitational search | |
| [en] In this paper, we address the problem of contact
state recognition for compliant motion robotic systems. The wrench (Cartesian forces and torques) and pose (position and orientation) of the manipulated object in different Contact Formations (CFs) are firstly captured during a certain task execution. Then for each CF, we develop an efficient Takagi- Sugeno (T-S) fuzzy inference system that can model that specific CF using the available input (wrench and pose) - output (the desired model output for each CF) data. The antecedent part parameters are computed using the Gravitational Search- based Fuzzy Clustering Algorithm (GS- FCA) and the consequent parts parameters are tuned by the Least Mean Square (LMS). Excellent mapping and hence recognition capabilities can be expected from the suggested scheme. In order to validate the approach; experimental test stand is built which is composed of a KUKA Light Weight Robot (LWR) manipulating a cube rigid object that interacts with an environment composed of three orthogonal planes. The manipulated object is rigidly attached to the robot arm. The robot is programmed, by a human operator, to move in different CFs and for each CF, the wrench and pose readings are captured via the Fast Research Interface (FRI) available at the KUKA LWR. Using the suggested approach, excellent modeling is obtained for different CFs during the robot task execution. A comparison with the available CF recognition approaches is also performed and the superiority of the suggested scheme is shown. | |
| Fonds National de la Recherche - FnR | |
| R-AGR-0071 > PROBE > 01/01/2013 - 31/12/2015 > PLAPPER Peter | |
| Researchers ; Professionals ; Students | |
| http://hdl.handle.net/10993/7635 | |
| FnR ; FNR2955286 > Ibrahim Jasim > > Self-adaptive Fuzzy Control for Robotic Peg-in-Hole Assembly Process > 01/05/2012 > 30/04/2016 > 2012 |
| File(s) associated to this reference | ||||||||||||||
|
Fulltext file(s):
| ||||||||||||||
All documents in ORBilu are protected by a user license.
