UWE Bristol Engineering showcase 2015

Jonathan Barnett
BEng Robotics
Project Supervisor
Prof. Alan Winfield
Analysing RoboGen for Evolutionary Design
Project summary
The aim of this project is the investigation of
the RoboGen software for the
implementation of evolutionary robotics.
The primary appeal of the RoboGen software is its
ability to co-evolve the robot body and brain
simultaneously, creating a more harmonious
design between the brain and body.
One of the key aspects of the RoboGen
software, is the ability to fully configure the
setup of the robot build. This data can then be
outputted to Matlab or other suitable software
for rendering the information allowing for a
generation by generation recount of the fitness
development.
The robot brain aspect evolves weights and biases
of the robot within the body structure derived
from the need to achieve the goal state, the design
of the robot brain system is described as a “fullyconnected,
recurrent artificial neural
network”(Auerbach et al., 2014). The limitations of
this robot brain are primarily based on the body
structure that it is contained within.
From Concept to Reality
The RoboGen software allows for the 3D
design of a robotic system using modular
parts pre-configured to be wired up. The
system then develops the artificial neural
network within this body in order to solve
the training scenario it has been placed in
Project Objectives
• Investigating the potential of the RoboGen
software for evolutionary neural network
development and co-evolutionary design
of both brain and body, in a variety of
situations examining the results that the
system outputs
• Investigation into the principle idea of real
world testing of fitness, being reintroduced
into the software population,
adjusting its fitness.
Project Conclusion
In conclusion the RoboGen software is a remarkable
application allowing for ease of use and accessible
introduction to the principles behind both
evolutionary neural network design and co-evolution
development between the brain and body of a robot.
The ability to configure a multitude of parameters as
well as different scenarios for testing means that the
software can be used for potentially multiple
problems depending on how complex the user makes
the terrain that the robot must navigate in order to
achieve its goals. The co-evolutionary nature
between both the brain and body of the robot, when
used, opens up a potential gateway towards true
independent design.