Aracna: An Open-Source Quadruped Platform for Evolutionary Robotics

Abstract

We describe a new, quadruped robot platform, Aracna, which requires non-intuitive motor commands in order to locomote and thus provides an interesting challenge for gait learning algorithms, such as those frequently developed in the Evolu-tionary Computation and Artificial Life communities. Aracna is an open-source hardware project composed of off-the-shelf and 3D-printed parts, enabling other research teams to mod-ify its design according to their scientific needs. Aracna was designed to overcome the shortcomings of a previous quadruped robot platform, whose legs were so heavy that the motors could not reliably execute the commands sent to them. We avoid this problem by locating all motors in the body core instead of on the legs and through a design which enables the servos to have a greater mechanical advantage. Specifically, each of the four legs has two joints controlled by separate four-bar linkage mechanisms that drive the pitch of the hip joint and knee joint. This novel design causes unconventional kinematics, creating an opportunity for gait-learning algorithms, which excel in counter-intuitive design spaces where human engineers tend to underperform. Be-cause it is low-cost, flexible, kinematically interesting, and and improvement over a previous design, Aracna provides a useful new hardware platform for testing algorithms that au-tomatically generate robotic behaviors.