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» Managing Complexity in Large Learning Robotic Systems
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ASPLOS
2009
ACM
14 years 8 months ago
Dynamic prediction of collection yield for managed runtimes
The growth in complexity of modern systems makes it increasingly difficult to extract high-performance. The software stacks for such systems typically consist of multiple layers a...
Michal Wegiel, Chandra Krintz
SEW
2003
IEEE
14 years 1 months ago
Model-Based Software Testing via Incremental Treatment Learning
Model-based software has become quite popular in recent years, making its way into a broad range of areas, including the aerospace industry. The models provide an easy graphical i...
Dustin Geletko, Tim Menzies
IROS
2009
IEEE
205views Robotics» more  IROS 2009»
14 years 2 months ago
Probabilistic categorization of kitchen objects in table settings with a composite sensor
— In this paper, we investigate the problem of 3D object categorization of objects typically present in kitchen environments, from data acquired using a composite sensor. Our fra...
Zoltan Csaba Marton, Radu Bogdan Rusu, Dominik Jai...
IROS
2007
IEEE
134views Robotics» more  IROS 2007»
14 years 2 months ago
Feature selection for grasp recognition from optical markers
Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...
KI
2010
Springer
13 years 6 months ago
CoTeSys - Cognition for Technical Systems
The COTESYS cluster of excellence1 investigates cognition for technical systems such as vehicles, robots, and factories. Cognitive technical systems (CTS) are information processi...
Martin Buss, Michael Beetz