Evolution of Biped Walking Using Neural Oscillators and Physical Simulation

Abstract

Controlling a biped robot with a high degree of freedom to achieve stable movement patterns is still an open and complex problem, in particular within the RoboCup community. Thus, the development of control mechanisms for biped locomotion have become an important field of research. In this paper we introduce a model-free approach of biped motion generation, which specifies target angles for all driven joints and is based on a neural oscillator. It is potentially capable to control any servo motor driven biped robot, in particular those with a high degree of freedom, and requires only the identification of the robot's physical constants in order to provide an adequate simulation. The approach was implemented and successfully tested within a physical simulation of our target system -the 19-DoF Bioloid robot. The crucial task of identifying and optimizing appropriate parameter sets for this method was tackled using evolutionary algorithms. We could show, that the presented approach is applicable in generating walking patterns for the simulated biped robot. The work demonstrates, how the important parameters may be identified and optimized when applying evolutionary algorithms. Several so evolved controllers were capable of generating a robust biped walking behavior with relatively high walking speeds, even without using sensory information. In addition we present first results of laboratory experiments, where some of the evolved motions were tried to transfer to real hardware.

Hierarchical Sliding Mode Algorithm for Athlete Robot Walking

“…Consider 0 = const > 0 the angle between one leg and the vertical axis when both legs touch the ground. Sample-time is defined as period time of a step of robot Many authors [25][26][27] proposed several solutions for designing the oscillators for the motion of two-legged walking robots. Their methods are very complex and based on intuition and developed by simulations and experiments.…”

Biped robot joint trajectory generation using PSO evolutionary algorithm

“…In model based we need to know exact information about dynamics of the robot such as its parts positions and their masses and define a model for evaluating and controlling stability of the robot. ZMP (Zero Moment Point) and inverted pendulum are two popular methods for this approach [3][4] [5].…”

Steps Toward a Modular Library for Turning Any Evolutionary Domain into an Online Interactive Platform

“…a controller for a biped walking robot (Hein et al, 2007;Reil and Husbands, 2002) typically will report the result, publish a version of the code, retire the experiment, and move on to new domains. Although the experimental results are indeed published, the ability to reproduce, observe, or extend those results generally requires considerable effort outside of the originating group.…”