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GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
13 years 11 months ago
Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming
We describe the first instance of an approach for control programming of humanoid robots, based on evolution as the main adaptation mechanism. In an attempt to overcome some of th...
Krister Wolff, Peter Nordin
GECCO
2004
Springer
115views Optimization» more  GECCO 2004»
13 years 11 months ago
Robotic Control Using Hierarchical Genetic Programming
In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canon...
Marcin L. Pilat, Franz Oppacher
ICRA
2010
IEEE
188views Robotics» more  ICRA 2010»
13 years 3 months ago
Classification and prediction for accurate sensor-based assembly to moving objects
Abstract-- Typical industrial assembly tasks require an accuracy that cannot be realized by only feedback control if a minimum speed is given by a conveyor. Feed-forward has proven...
Friedrich Lange, Johannes Scharrer, Gerd Hirzinger
ECP
1997
Springer
128views Robotics» more  ECP 1997»
13 years 10 months ago
SINERGY: A Linear Planner Based on Genetic Programming
In this paper we describe SINERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world...
Ion Muslea
TROB
2010
129views more  TROB 2010»
13 years 4 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...