It is considered a difficult task to design a controller from scratch for a robot in a dynamic environment. Evolutionary and genetic algorithms are frequently used to find a solution with desired properties. The evolution is supposed to run on one robot or agent processor. In this article we explore the possibility of dividing the genome among several robots. Robots exchange among each other su...

Computation of a collision-free path for a movable object among obstacles is an important problem in the fields of robotics. The simplest version of motion planning consists in generating a collisionfree path for a movable object among known and static obstacles. In this paper, we introduce a two stages evolutionary algorithm. The first stage is designed to compute a collission-free path in a k...

In this paper we present the development of a method that combines the evolutionary robotics approach with action selection. A collection task is set in an arena where a Khepera robot has to collect cylinders that simulate food. Furthermore, two basic motivations, labeled as ‘fear’ and ‘hunger’, both affect the selection of the behavioral repertoire. In this paper we propose an initial evolutio...

In many cases, a real robot application requires the navigation in dynamic environments. The navigation problem involves two main tasks: to avoid obstacles and to reach a goal. Generally, this problem could be faced considering reactions and sequences of actions. For solving the navigation problem a complete controller, including actions and reactions, is needed. Machine learning techniques has...

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have ...

* 0-7803-7952-7/03/$17.00  2003 IEEE. Abstract In this paper we describe a method for the synthesis of robotic controllers using evolutionary techniques. A modified version of the recurrent neural network used for controlling the robots is evolved using Genetic Algorithm using the Variable Length Genotype approach where the genotype encodes the network. It has been discovered that separation o...

This article presents a method, which enables an autonomous mobile robot to create an internal representation of the external world. The elements of this internal representation are the dynamical features of a neuro-controller and their time regime during the interaction of the robot with its environment. As an examples of this method the behavior of a Khepera robot is studied, which is control...

The GUARDIANS robot swarm is selforganising and can be seen as a hybrid of a (heterogeneous) swarm, a mobile ad-hoc network and an (evolving) topological map of the environment. We assume that robots cooperate in order to deploy themselves, search the area and construct a (online) map of the environment. We present a novel approach of distributing robots on site that takes advantage of a cooper...

1 Corresponding author. Abstract Based on a neuroscientific hypothesis, this paper explores the possibility of an ‘inner world’ based on internal simulation of perception. We present three sets of experiments with a possible minimal model, using a simulated Khepera robot controlled by a simple recurrent connectionist network. Using an evolutionary algorithm the robots are trained on increasingl...

For several years now, various researchers have endeavored to apply artificial evolution to the automatic design of control systems for real robots. One of the major challenges they face concerns the question of how to assess the fitness of evolving controllers when each evolutionary run typically involves hundreds of thousands of such assessments. This article outlines new ways of thinking abo...