Optimization and learning in neural networks for formation and control of coordinated movement
Attention and performance XIV (silver jubilee volume)
Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
Multiple model-based reinforcement learning
Neural Computation
Local Dimensionality Reduction for Locally Weighted Learning
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Biologically inspired robot behavior engineering
Incremental Learning of Linear Model Trees
Machine Learning
MOSAIC Model for Sensorimotor Learning and Control
Neural Computation
Springer Handbook of Robotics
Adaptive Optimal Control for Redundantly Actuated Arms
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
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We present a model of motor learning based on a combination of Operational Space Control and Optimal Control. Anticipatory processes are used both in the learning of the dynamics model of the system and in the coordination between both types of control. In order to illustrate the proposed model and associated control method, we apply these principles to the control of a simplified virtual humanoid performing a stand-up task starting from a crouching posture.