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The aim of the project described in this paper was to investigate robot learning at a most fundamental level. The project focused on the transition between organisms with innate behaviors and organisms that have the most rudimentary capability of learning through their personal interaction with...
This paper addresses the localization and mapping problem for a robot moving through a (possibly) unknown environment where indistinguishable landmarks can be detected. A set theoretic approach to the problem is presented. Computationally efficient algorithms for measurement-to-feature matching,...
In recent decades the research on Evolutionary Robotics (ER) has developed rapidly. This direction is primarily concerned with the use of evolutionary computing techniques in the design of intelligent and adaptive controllers for robots. Meanwhile, much attention has been paid to a new set of...
This work describes a color Vision-based System intended to perform stable autonomous driving on unmarked roads. Accordingly, this implies the development of an accurate road surface detection system that ensures vehicle stability. Although this topic has already been documented in the technical...
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are demonstrated through a succession of increasingly complex experiments. Starting from the learning of simple reactive...
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