DocumentCode
2343150
Title
A learning framework for generic sensory-motor maps
Author
Lopes, Manuel ; Damas, Bruno
Author_Institution
Inst. de Sistemas e Robotica, Lisbon
fYear
2007
fDate
Oct. 29 2007-Nov. 2 2007
Firstpage
1533
Lastpage
1538
Abstract
We present a new approach to cope with unknown redundant systems. For this we present i) an online algorithm that learns general input-output restrictions and, ii) a method that, given a partial set of input-output variables, provides an estimate of the remaining ones, using the learned restrictions. We show applications of the algorithm using examples of direct and inverse robot kinematics.
Keywords
robot kinematics; direct robot kinematics; general input-output restrictions; generic sensory-motor maps; inverse robot kinematics; learning framework; redundant systems; Acoustic sensors; Humanoid robots; Intelligent robots; Inverse problems; Motor drives; Notice of Violation; Robot control; Robot kinematics; Trajectory; USA Councils; humanoid robots; manifold learning; redundancy; sensory-motor coordination;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on
Conference_Location
San Diego, CA
Print_ISBN
978-1-4244-0912-9
Electronic_ISBN
978-1-4244-0912-9
Type
conf
DOI
10.1109/IROS.2007.4399566
Filename
4399566
Link To Document