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» Control Model Learning for Whole-Body Mobile Manipulation
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ECAI
2004
Springer
14 years 3 days ago
Avatars That Learn How to Behave
It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
Adam Szarowicz, Paolo Remagnino
ICRA
2002
IEEE
148views Robotics» more  ICRA 2002»
13 years 11 months ago
A Neural Approach to Adaptive Behavior and Multi-Sensor Action Selection in a Mobile Device
Sampling multisensory information and taking the appropriate motor action is critical for a biological organism’s survival, but a difficult task for robots. We present a Neurally...
Jeffrey L. Krichmar, James A. Snook
ESANN
2001
13 years 8 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
CORR
2006
Springer
101views Education» more  CORR 2006»
13 years 6 months ago
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...
CDC
2008
IEEE
171views Control Systems» more  CDC 2008»
14 years 1 months ago
Constrained optimal control theory for differential linear repetitive processes
Abstract. Differential repetitive processes are a distinct class of continuous-discrete twodimensional linear systems of both systems theoretic and applications interest. These pr...
Michael Dymkov, Eric Rogers, Siarhei Dymkou, Krzys...