Evolutionary Robotics from Intelligent Robots to Artificial Life

From Life to Robotics: Social Robots

The formation of groups is of essential importance in biology. Aggregation is based on a simple dynamical model for the motion of each individual. It is shown that a swarm is formed within a short time span and is stable under perturbations.

How to Evolve Autonomus Robots: Different Approaches in Evolutionary Robotics

How to Evolve Autonomous Robots: Different Approaches in Evolutionary Robotics

number of parts or modules within the system; rather, it scales with the number of possible interactions between parts and modules. A methodology for evolving the control systems of autonomous robots has not yet been well established. In this paper we will show different examples of applications of evolutionary robotics to real robots by describing three different approaches to develop neural c...

Bio-Inspired Technique to Produce Strong Competitors for Studies in Artificial-life and Evolutionary Robotics

In both Artificial-Life (A-Life) studies and in Evolutionary Robotics (ER) the use of bio-inspired evolutionary computation methods is wide. The majority of such studies either use knowledge-base aggregate fitness, or some game definition, to drive the selection. Often the bio-inspired evolution suffers from the bootstrap problem, in which randomly initialized populations have no detectable lev...

Networked Robots: from Telerobotics to Cloud Robotics

As of 2013, almost all robots have access to computer networks that offer extensive computing, memory, and other resources that can dramatically improve performance. The underlying enabling framework is the focus of this chapter: networked robots. Networked robots trace their origin to telerobots, or remotely controlled robots. Telerobots are widely used to explore undersea terrains and outer s...