A biologically consistent model of legged locomotion gaits

Abstract

Significant advances have occurred over the past two decades in issues related to the mechanical design of legged robots and the coordination and control of legs during locomotion. The performance of current legged robots, however, remains far below even simplest counterparts in the biological world. Naturally, this has led to a search by researchers for biologically motivated approaches to the design and control of legged robots in order to improve their performance and robustness. In this paper the use of central pattern generators (CPGs) will be examined for the control of locomotion. In doing so, a biologically consistent mathematical model that has the ability to emulate arbitrary gaits is developed. A simple algorithm for encoding the characteristic gaits of bipeds, quadrupeds and hexapeds is presented. The paper concludes with a brief description of a locomotion control architecture for actually realizing leg movements that correspond to various gaits.

Modular neuroevolution for multilegged locomotion

“…groups of neurons that produce oscillatory signals for locomotion [27]. CPGs are typically implemented as CTRNNs, using leaky integrator neurons.…”

Evolving Symmetry for Modular System Design

“…For example, a bilaterally symmetric animal has identical left and right legs that are constrained to be equidistant from its plane of symmetry, and the symmetric neural circuitry controlling its locomotion has identical modules constrained by the nature of their interconnections [11]. Symmetry in such systems can potentially provide two benefits: (1) it allows encoding identical subsystems compactly using a common set of genes [1,32,43] for easier evolutionary search and (2) it can result in patterned oscillations in neural circuits [11,25,47], e.g. for effective gaits.…”