4 research outputs found
How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations
In this paper, we address the problem of deploying a wire along a specific path selected by an unskilled user. The robot has to
learn the selected path and pass a wire through the peg table by using the same tool. The main contribution regards the hybrid use
of Cartesian positions provided by a learning procedure and joint positions obtained by inverse kinematics and motion planning.
Some constraints are introduced to deal with non-rigid material without breaks or knots. We took into account a series of metrics
to evaluate the robot learning capabilities, all of them over performed the targets
Theoretical Interpretations and Applications of Radial Basis Function Networks
Medical applications usually used Radial Basis Function Networks just as Artificial Neural Networks. However, RBFNs are Knowledge-Based Networks that can be interpreted in several way: Artificial Neural Networks, Regularization Networks, Support Vector Machines, Wavelet Networks, Fuzzy Controllers, Kernel Estimators, Instanced-Based Learners. A survey of their interpretations and of their corresponding learning algorithms is provided as well as a brief survey on dynamic learning algorithms. RBFNs' interpretations can suggest applications that are particularly interesting in medical domains