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» Control Model Learning for Whole-Body Mobile Manipulation
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ECAI
2004
Springer
15 years 9 months 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»
15 years 9 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
15 years 5 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»
15 years 4 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,...
158
Voted
CDC
2008
IEEE
171views Control Systems» more  CDC 2008»
15 years 10 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...