Visual Target Sequence Prediction via Hierarchical Temporal Memory Implemented on the iCub Robot
Murat Kirtay, Egidio Falotico, Alessandro Ambrosano, Ugo Albanese, Lorenzo Vannucci, Cecilia Laschi
Biomimetic and Biohybrid Systems
Volume 9793 of the series Lecture Notes in Computer Science pp 119-130
Date: 12 July 2016
Abstract
In this article, we present our initial work on sequence prediction of a visual target by implementing a cortically inspired method, namely Hierarchical Temporal Memory (HTM). As a preliminary test, we employ HTM on periodic functions to quantify prediction performance with respect to prediction steps. We then perform simulation experiments on the iCub humanoid robot simulated in the Neurorobotics Platform. We use the robot as embodied agent which enables HTM to receive sequences of visual target position from its camera in order to predict target positions in different trajectories such as horizontal, vertical and sinusoidal. The obtained results indicate that HTM based method can be customized for robotics applications that require adaptation of spatiotemporal changes in the environment and acting accordingly.
Available behind Springer paywall here. Most of the chapter can be read in Google Books