This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control po...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
— In this paper, we describe the implementation of a precise reaching controller on an upper-torso humanoid robot. The solution we propose does not rely on prior models of the ki...
Francesco Nori, Lorenzo Natale, Giulio Sandini, Gi...
This paper discusses the emergence of sensorimotor coordination for ESCHeR, a 4DOF redundant foveated robot-head, by interaction with its environment. A feedback-error-learning(FEL...
Robotic controllers take advantage from neural network learning capabilities as long as the dimensionality of the problem is kept moderate. This paper explores the possibilities of...
The work presented in this paper is part of the development of a robotic system able to learn context dependent visual clues to navigate in its environment. We focus on the obstacl...