Learning gaits for the Stiquito

Published 22 November 2002

Gary B. Parker, David W. Braun, I. Cyliax

DOI10.1109/icar.1997.620196

Citations12

TL;DR

Tests on the actual semi-autonomous robot showed that after 1000 generations gaits comparable to the best designed by human engineers were produced.

Abstract

It has been shown that the use of cyclic genetic algorithms can be an effective means of gait generation for hexapod robot simulations. They can, with only low-level primitives, produce reasonable gaits in minimal time. In addition, their output requires little in intermediate controller complexity as it is a sequence of these primitives, which can be fed directly into the robot. In this paper, we test the applicability of these algorithms on an actual robot. A model for simulation was produced based on the measured capabilities of the Stiquito robot. This model was trained with the CGA using five random initial populations; gaits quickly evolved for all five. Tests on the actual semi-autonomous robot showed that after 1000 generations gaits comparable to the best designed by human engineers were produced.

Keywords

Computer ScienceEngineering

The MIT Press eBooksAdaptation in Natural and Artificial Systems

35,568 Citations1992John H. Holland

Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.

The MIT Press eBooksAdvances in Genetic Programming

721 Citations1996

This third volume of Advances in Genetic Programming highlights many of the recent technical advances in this increasingly popular field.

Neural ComputationA Robot that Walks; Emergent Behaviors from a Carefully Evolved Network

549 Citations1989Rodney A. Brooks

Adaptive BehaviorEvolving Dynamical Neural Networks for Adaptive Behavior

506 Citations1992Randall D. Beer, John C. Gallagher

It is demonstrated that continuous-time recurrent neural networks are a viable mechanism for adaptive agent control and that the genetic algorithm can be used to evolve effective neural controllers.

Robotics and Autonomous SystemsApplication of evolved locomotion controllers to a hexapod robot

150 Citations1996John C. Gallagher, Randall D. Beer +2 more

This paper shows that genetic algorithms used to evolve dynamical neural networks for controlling the locomotion of a simulated hexapod agent are capable of directing the walking of a real six-legged robot, and that many of the desirable properties observed in simulation carry over directly to the real world.

CYCLIC GENETIC ALGORITHMS FOR THE LOCOMOTION OF HEXAPOD ROBOTS

47 Citations2008Gary B. Parker, J. E. Rawlins

Cyclic Genetic Algorithms are introduced, which were developed precisely for adaptive gait development for hexapod robots, and can be applied to other robotics domains.

Birkhäuser Boston eBooksReal-Time Control of Walking

44 Citations1986Marc Donner