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» Learning humanoid reaching tasks in dynamic environments
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SARA
2007
Springer
15 years 3 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto
IDA
2003
Springer
15 years 2 months ago
A Semi-supervised Method for Learning the Structure of Robot Environment Interactions
For a mobile robot to act autonomously, it must be able to construct a model of its interaction with the environment. Oates et al. developed an unsupervised learning method that pr...
Axel Großmann, Matthias Wendt, Jeremy Wyatt
HPCC
2009
Springer
14 years 7 months ago
Graph-Based Task Replication for Workflow Applications
Abstract--The Grid is an heterogeneous and dynamic environment which enables distributed computation. This makes it a technology prone to failures. Some related work uses replicati...
Raúl Sirvent, Rosa M. Badia, Jesús L...
JUCS
2008
163views more  JUCS 2008»
14 years 9 months ago
Authoring Social-aware Tasks on Active Spaces
: Social-aware computing is an emerging trend based on ubiquitous computing technologies and collaborative work. A successful design demands a better understanding of group tasks, ...
Roberto F. Arroyo, Miguel Gea, José Luis Ga...
ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
14 years 8 months ago
Biomimetic motor behavior for simultaneous adaptation of force, impedance and trajectory in interaction tasks
— Interaction of a robot with dynamic environments would require continuous adaptation of force and impedance, which is generally not available in current robot systems. In contr...
Ganesh Gowrishankar, Alin Albu-Schäffer, Haru...